Source: https://patents.google.com/patent/JP6552979B2/en
Timestamp: 2020-06-01 20:19:01
Document Index: 508715591

Matched Legal Cases: ['art 12', 'art 13', 'art 11', 'art 12', 'art 13', 'art 14', 'art 15']

JP6552979B2 - Image processing device, warning device, image processing system, and image processing method - Google Patents
Image processing device, warning device, image processing system, and image processing method Download PDF
JP6552979B2
JP6552979B2 JP2016026926A JP2016026926A JP6552979B2 JP 6552979 B2 JP6552979 B2 JP 6552979B2 JP 2016026926 A JP2016026926 A JP 2016026926A JP 2016026926 A JP2016026926 A JP 2016026926A JP 6552979 B2 JP6552979 B2 JP 6552979B2
JP2016026926A
JP2017146711A (en
英春 服部
喜文 泉
2016-02-16 Application filed by 株式会社日立製作所 filed Critical 株式会社日立製作所
2016-02-16 Priority to JP2016026926A priority Critical patent/JP6552979B2/en
2017-08-24 Publication of JP2017146711A publication Critical patent/JP2017146711A/en
2019-07-31 Publication of JP6552979B2 publication Critical patent/JP6552979B2/en
238000003672 processing method Methods 0 title claims description 4
238000004458 analytical methods Methods 0 claims description 75
The present invention relates to an image processing apparatus, a warning apparatus, an image processing system, and an image processing method.
In recent years, it has been proposed to detect on-road appendages in an image using an image captured by an imaging device such as a smartphone or a drive recorder. For example, Patent Document 1 discloses a technology for recognizing a road sign from an image captured by a camera installed in a vehicle and notifying a driver of information of a recognition result.
JP 2008-139320 A
Road signs include a combination of main signs indicating various regulations, instructions, warnings, guidance and the like to be notified to the driver, and auxiliary signs supplementing the meaning and content of the signs. When there are multiple road signs that combine these signs and auxiliary signs in the captured image, each road sign is recognized by correctly judging which auxiliary sign corresponds to which main sign. There is a need. However, the technique described in Patent Document 1 does not particularly take this point into consideration. Therefore, depending on the position and orientation of the road sign, the correct combination of the main sign and the auxiliary sign cannot be determined, and the road sign may not be recognized correctly.
An image processing apparatus according to a first aspect of the present invention includes a contrast correction unit that generates a contrast correction image that corrects contrast of an input image captured by an on-vehicle camera mounted on a vehicle, and a color of the input image. A color analysis unit that creates a color correction image, and an object detection that detects a main sign included in the input image based on the brightness correction image and detects an auxiliary sign included in the input image based on the color correction image And the main sign and the auxiliary sign are associated with each other on the basis of the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit. recognizing object-related analysis unit road signs that combine to obtain the position of the road sign, on the basis of the cumulative result of the position of the road sign acquired, it determines the reliability of the road signs Comprising a Yoriyukido judging unit.
An image processing apparatus according to a second aspect of the present invention includes a brightness correction unit that generates a brightness correction image in which brightness and brightness of an input image captured by an on-vehicle camera mounted on a vehicle is corrected; A color analysis unit that creates a color correction image, and an object detection that detects a main sign included in the input image based on the brightness correction image and detects an auxiliary sign included in the input image based on the color correction image And the main sign and the auxiliary sign are associated with each other on the basis of the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit. An object-related analysis unit that recognizes a road sign combined with the image, and the brightness correction unit sets a target area within a predetermined range of the input image, and the past image captured before the input image. Wherein the average value of the brightness of the color in the region corresponding to the target region, based on the brightness average value of the color of the target area of the input image, to create the brightness correction image.
An image processing apparatus according to a third aspect of the present invention includes a contrast correction unit that generates a contrast correction image that corrects contrast of an input image captured by an on-vehicle camera mounted on a vehicle, and a color of the input image. A color analysis unit that creates a color correction image, and an object detection that detects a main sign included in the input image based on the brightness correction image and detects an auxiliary sign included in the input image based on the color correction image And the main sign and the auxiliary sign are associated with each other on the basis of the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit. An object-related analysis unit that recognizes a road sign combined with the color image, the color analysis unit sets a target area in a predetermined range of the input image, and sets a color difference value in the target area of the input image. Zui and creates the color correction image.
An image processing apparatus according to a fourth aspect of the present invention is a light and dark correction unit that generates a light and dark corrected image in which light and dark of an input image captured by an on-vehicle camera mounted on a vehicle is corrected; A color analysis unit that creates a color correction image, and an object detection that detects a main sign included in the input image based on the brightness correction image and detects an auxiliary sign included in the input image based on the color correction image And the main sign and the auxiliary sign are associated with each other on the basis of the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit. An object-related analysis unit that recognizes a road sign in combination with each other, and the object detection unit sets target regions in predetermined areas of the input image and the contrast correction image, respectively, The average value of the brightness of the colors in the region corresponding to the target region of the past image taken before the image and the average value of the brightness of the colors in the target region of the input image are respectively specified The threshold is set based on the weighted average value weighted average by the weight of d, a first separated image is created from the light and dark correction image using the threshold, and a rectangular portion corresponding to the auxiliary marker is generated from the color correction image A second separated image is extracted to extract the main sign and the auxiliary sign by comparing a preset reference image with the first separated image and the second separated image, respectively. Detect each.
The warning device according to the present invention includes an image processing device, and a warning output unit that outputs a warning for the driver of the vehicle based on the recognition result of the road sign by the image processing device.
An image processing system according to the present invention includes a terminal device mounted on a vehicle and a server device that communicates with the terminal device, and the terminal device is photographed by an in-vehicle camera mounted on the vehicle. Included in the input image based on the light and dark correction image, a light and dark correction unit for generating a light and dark correction image in which the light and dark correction of the input image is corrected, a color analysis unit for generating a color correction image in which the color of the input image is corrected, An object detection unit that detects a main sign to be detected and detects an auxiliary sign included in the input image based on the color correction image; and a detection result indicating a detection result of the main sign and the auxiliary sign by the object detection unit An image transmission unit that transmits an image to the server device, the server device receiving the post-detection image transmitted from the terminal device, and the detection received by the image reception unit. A second contrast correction unit that creates a contrast correction image that corrects contrast of the subsequent image; and a second color analysis unit that creates a color correction image that corrects the color of the after detection image received by the image reception unit A second object detection unit that detects a main sign included in the post-detection image based on the brightness correction image, and detects an auxiliary sign included in the post-detection image based on the color correction image; Based on the positional relationship between the main marker and the auxiliary marker in the post-detection image received by the receiving unit, the main marker and the auxiliary marker are associated with each other, thereby combining the main marker and the auxiliary marker. And an object related analysis unit that recognizes the road sign.
An image processing method according to the present invention is a method of processing an input image captured by an on-vehicle camera mounted on a vehicle and input to a computer, wherein the computer sets a target area in a predetermined range of the input image. Based on an average value of color brightness in an area corresponding to the target area of a past image captured before the input image and an average value of color brightness in the target area of the input image Te, creates a brightness corrected image obtained by correcting the brightness of the input image, based on the color difference value of the target area of the input image, creates a color correction image obtained by correcting the color of the input image, the brightness A main sign included in the input image is detected based on the corrected image, an auxiliary sign included in the input image is detected based on the color corrected image, and the input image of the detected main sign and the auxiliary sign is detected. Based on the positional relationship of the inner, the by associating the label with the auxiliary label each other, recognize road signs that combine the present indicator and said auxiliary label.
According to the present invention, it is possible to correctly recognize a road sign that is a combination of this sign and an auxiliary sign.
It is a block diagram showing functional composition of an image processing device concerning a 1st embodiment of the present invention. It is a figure showing the example of hardware constitutions of the image processing device concerning a 1st embodiment of the present invention. FIG. 6 is a diagram for explaining an example of the operation of a color space conversion unit. It is a figure for demonstrating an example of operation | movement of the brightness correction | amendment part. It is a figure for demonstrating an example of operation | movement of a color analysis part. It is a figure for demonstrating an example of operation | movement of an object detection part. It is a figure for demonstrating an example of operation | movement of an object detection part. It is a figure for demonstrating an example of operation | movement of an object related analysis part. It is a figure for demonstrating an example of operation | movement of an object related analysis part. It is a figure for demonstrating an example of operation | movement of a direction determination part. It is a figure for demonstrating an example of operation | movement of a reliability determination part. It is a figure for demonstrating an example of operation | movement of a drawing part. It is a flowchart for demonstrating the operation | movement of the image processing apparatus by the 1st Embodiment of this invention. It is a block diagram showing composition of a warning device concerning a 2nd embodiment of the present invention. It is a block diagram which shows the structure of the image processing system which concerns on the 3rd Embodiment of this invention. It is a block diagram which shows the structure of the image processing system which concerns on the 4th Embodiment of this invention. It is a block diagram showing composition of an image processing system concerning a 5th embodiment of the present invention.
First, the outline of the present invention will be described below.
Generally, in order to provide information on road attachments such as road signs as additional information such as map information, there are road attachments in advance for all routes where vehicles may travel. It is necessary to investigate whether it will be expensive or expensive. In addition, there is also a problem that the additional information can not be reflected on the map information in a timely manner for the newly added road and the road accessories on the road that has been changed due to the construction. Therefore, in the embodiment of the present invention described below, road accessories are timely extracted from images taken by a large number of unspecified users using, for example, in-vehicle terminals such as smart phones, drive recorders, and car navigation devices. It is possible to detect.
By the way, there may be a plurality of road signs combining the present sign and the auxiliary sign in the image taken by the in-vehicle terminal. In such a case, the correct sign information cannot be notified to the user unless the correct combination of the main sign and the auxiliary sign is required. In some cases, a traveling direction sign and a sign other than the traveling direction are attached to the same sign post. Even in such a case, the correct sign information cannot be notified to the user unless the signs of the traveling direction and the signs other than the traveling direction can be correctly distinguished. In particular, in the technique of the above-mentioned Patent Document 1, when a plurality of main signs and auxiliary signs are detected, a correct combination of the main signs and auxiliary signs cannot be obtained. Since signs other than directions cannot be distinguished, there is a problem that correct sign information cannot be notified to the user. Therefore, in the embodiment of the present invention described below, a technique for detecting a desired target in an image captured by an on-vehicle terminal and enabling determination of a combination of the targets and identification of the direction of the target. Propose.
In addition, the embodiment of the present invention separates the background in the image from the object in the background even when the brightness of the captured image changes, and detects the object in the background and determines the combination of the objects. And an image processing apparatus and method for realizing identification of the orientation of an object.
<Functional configuration of image processing apparatus>
FIG. 1 is a block diagram showing a functional configuration of an image processing apparatus 1 according to the first embodiment of the present invention. As shown in FIG. 1, the image processing apparatus 1 functions as an input unit 10, a color space conversion unit 11, a light / dark correction unit 12, a color analysis unit 13, an object detection unit 14, and an object-related analysis. Unit 15, orientation determination unit 16, reliability determination unit 17, drawing unit 18, recording unit 19, image storage unit 90, and control unit 91. Each function of the image processing apparatus 1 shown in FIG. 1 is realized by combining various programs and hardware in an information device such as a portable mobile terminal device such as a smart phone, a personal computer, and a server device.
The input unit 10 externally acquires an input image to be processed in the image processing apparatus 1. Data of an image taken by an in-vehicle camera (not shown) mounted on the vehicle is input to the input unit 10 as an input image at predetermined time intervals. In addition, you may use the camera which portable drive terminal apparatuses, such as a drive recorder installed in the vehicle and a smart phone, have as a vehicle-mounted camera. Moreover, you may use the picked-up image of the vehicle-mounted camera acquired via the information communication network and recording medium not shown as an input image. The input image may be a still image, or an arbitrary frame in a moving image may be extracted and used as an input image. As a still image data format, for example, JPEG, JPEG2000, PNG, BMP or the like is used. On the other hand, as a data format of moving images, for example, Motion JPEG, MPEG, H.264, H.264, HD / SDI, etc. are used.
The color space conversion unit 11 acquires color brightness information in the input image by converting the color space of the input image.
The contrast correction unit 12 uses the brightness information of the color of the past input image stored in the image storage unit 90 and the brightness information of the color of the current input image obtained by the color space conversion unit 11. Then, the brightness change amount of the color of the current input image is obtained, and an image in which the brightness of the input image is corrected is created based on the brightness change amount. Hereinafter, an image created by the light / dark correction unit 12 is referred to as a light / dark correction image.
The color analysis unit 13 creates an image in which the color of the input image is corrected by analyzing the relationship of colors in each pixel of the input image using the difference value of the primary colors and the threshold for color analysis. Hereinafter, the image generated by the color analysis unit 13 is referred to as a color correction image.
The object detection unit 14 detects a main sign and an auxiliary sign of a road sign included in the input image using the light / dark correction image created by the light / dark correction part 12 and the color correction image created by the color analysis part 13. Detect as a target object. Specifically, the object detection unit 14 obtains a threshold for separating the main mark from the light and dark correction image, and uses the threshold to separate the background and the main mark in the light and dark correction image. Further, by detecting a rectangular object corresponding to the auxiliary sign from the color correction image, the background and the auxiliary sign in the color correction image are separated. In this way, the main sign and the auxiliary sign are extracted from the brightness correction image and the color correction image, respectively, and compared with a preset reference image, thereby detecting the main sign and the auxiliary sign.
The object relation analysis unit 15 analyzes the relation between these objects based on the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit 14. As a result, the road sign is recognized by combining the main sign and the auxiliary sign determined to be highly relevant.
The direction determination unit 16 determines the directions of the main mark and the auxiliary mark detected by the object detection unit 14 and determines whether these are road signs related to the traveling direction of the vehicle.
The reliability determination unit 17 acquires and accumulates the positions of the main marker and the auxiliary marker detected by the object detection unit 14, and determines the reliability of these road markers based on the accumulation result.
The drawing unit 18 draws a detection frame that surrounds these objects on the input image for the main sign and the auxiliary sign detected by the object detection unit 14. The image in which the detection frame is drawn by the drawing unit 18 is an image showing the detection result of the main marker and the auxiliary marker by the object detection unit 14, and hence this image is hereinafter referred to as a post-detection image.
The recording unit 19 stores the post-detection image created by the drawing unit 18 in the image storage unit 90 and saves it. The image after detection is also output from the image processing apparatus 1 to the outside.
The control unit 91 is connected to each component of the image processing apparatus 1 described above, and controls these operations. Note that each component may operate autonomously as necessary without being controlled by the control unit 91.
<Hardware Configuration of Image Processing Device>
FIG. 2 is a diagram illustrating a hardware configuration example of the image processing apparatus 1 according to the first embodiment of the present invention. As illustrated in FIG. 2, the image processing apparatus 1 includes a CPU 201, a memory 202, a storage device 203, an output device 204, an input device 205, and a communication device 206, which are connected via a bus 207. Connected to each other.
The CPU 201 is a processor that reads various programs from the memory 202 as necessary and executes processing according to the programs. By the processing executed by the CPU 201, the input unit 10, the color space conversion unit 11, the brightness correction unit 12, the color analysis unit 13, the object detection unit 14, the object relation analysis unit 15, the orientation determination unit 16, and the reliability Respective functional configurations of the determination unit 17, the drawing unit 18, the recording unit 19, and the control unit 91 are realized.
The memory 202 stores various programs read by the CPU 201 and temporarily stores various data used in processing being executed by the CPU 201 as necessary.
The storage device 203 is a device that stores various data used in the image processing apparatus 1 and corresponds to the image storage unit 90 described with reference to FIG. The storage device 203 stores, for example, the aforementioned input image, brightness correction image, color correction image, reference image, post-detection image, and the like. In addition, past input images are also stored in the storage device 203.
The output device 204 is a device for outputting a post-detection image, and is composed of devices such as a display, a printer, and a speaker. For example, when a display is used as the output device 204, the post-detection image generated by the drawing unit 18 is displayed on the display screen.
The input device 205 is a device for inputting a user's instruction and the like, and includes devices such as a keyboard, a mouse, and a microphone. For example, an input image to be processed in the image processing apparatus 1 is determined in accordance with a user instruction via the input device 205.
The communication device 206 is a device for communicating with another device. For example, the communication device 206 can be used to receive an input image transmitted from an on-vehicle camera, and transmit and receive various data to and from a server apparatus connected via a network. The communication device 206 may be connected to the image processing apparatus 1 without using the communication device 206 in the image processing apparatus 1.
<Configuration and operation of each part>
Next, the color space conversion unit 11, the light / dark correction unit 12, the color analysis unit 13, the object detection unit 14, the object related analysis unit 15, the orientation determination unit 16, the reliability determination unit 17, the drawing unit 18, and the recording unit 19. The operation of each functional configuration will be described in detail below.
(I) Color space converter 11
The color space conversion unit 11 generates, for example, an image obtained by converting the RGB color space of the input image into the Lab color space as color brightness information in the input image. The L value, a value, and b value for the input image are acquired by Lab color space conversion. Note that the L value is information corresponding to lightness, and the a value and b value are information indicating the brightness of the color.
FIG. 3 is a diagram for explaining an example of the operation of the color space conversion unit 11. In FIG. 3, an image N on the left side shows an example of an input image expressed in the RGB color space, and an image NA on the right side shows an example of the input image after color space conversion expressed in the Lab color space. These images include the sign 31, the auxiliary sign 32, and the road 33. The image NA after color space conversion obtained by the color space conversion unit 11 is stored in the image storage unit 90.
(Ii) light and dark correction unit 12
The brightness correction unit 12 uses the brightness information of the color of the input image after color space conversion determined by the color space conversion unit 11, that is, at least one of the a value and the b value, as described below. Create a corrected image.
FIG. 4 is a diagram for explaining an example of the operation of the contrast correction unit 12. In FIG. 4, an image (N-1) on the left side shows an example of an image obtained by converting the color space of the input image (N-1) acquired in the past, and an image NA on the right side is the same as FIG. An image example obtained by converting the color space of the input image N is shown. Further, an image NB on the lower right side shows an example of an image after light and dark correction.
The light / dark correction unit 12 sets a light / dark correction target region R2 for a predetermined range of the image NA, and calculates an average value aveR2 of the color information (a value or b value) in the region R2 of the image NA. This average value aveR2 corresponds to the average value of the brightness of the color in the region R2 of the input image N. The position and shape of the region R2 can be preset as a range in which the road sign should be present in the image NA, based on the mounting position of the on-vehicle camera, the shooting direction, the angle of view, and the like.
Further, the contrast correction unit 12 sets a target region R1 of contrast correction corresponding to the above region R2 to the image (N-1) A, and color information in the region R1 of the image (N-1) A An average value aveR1 of (a value or b value) is calculated. This average value aveR1 corresponds to the average value of the brightness of the color in the region R2 of the past input image (N-1). The position and the shape of the region R1 may be the same as the region R2, or the moving distance of the vehicle from acquisition of the past input image (N-1) to acquisition of the current input image N It may be determined in consideration.
After calculating the average values aveR2 and aveR1, the light / dark correction unit 12 calculates a magnification value v for creating a light / dark correction image using the following equation (1).
V = E2 / E1 (1)
In the formula (2), E1 and E2 represent either the average value aveR2 or aveR1, respectively. Specifically, when aveR1 ≧ aveR2, E1 = aveR2 and E2 = aveR1. On the other hand, when aveR1 <aveR2, E1 = aveR1 and E2 = aveR2. Alternatively, the magnification value v may be a fixed value.
After calculating the magnification value v, next, the brightness correction unit 12 obtains the brightness value cnCor of the color after the brightness correction for each pixel in the region R2 of the image NA using the following equation (2). In Equation (2), cn represents the a value or the b value of each pixel in the region R2 of the image NA.
cnCor = cn- (aveR2-cn) * v (2)
By calculating the brightness value cnCor of the corrected color for each pixel in the area R2 of the image NA by the above equation (2), the pixel darker than the average is darker and the pixel brighter than the average is calculated. The contrast of the image NA can be corrected to be brighter. By performing such correction, even if the main mark 31 to be detected is buried in the background and hard to be seen in the image NA as it is, it can be easily detected in the subsequent processing.
The brightness correction unit 12 corrects the brightness of the image NA by calculating the cnCor value for each pixel in the region R2 of the image NA by the processing described above, and creates the brightness correction image NB.
(Iii) Color analysis unit 13
The color analysis unit 13 calculates the color difference value of the input image as follows, and creates a color correction image using the color difference value.
FIG. 5 is a diagram for explaining an example of the operation of the color analysis unit 13. 5, an image N on the left side shows an example of an input image represented in the RGB color space, and an image MB on the right side shows an image example after color correction, as in FIG.
The color analysis unit 13 sets a target region R2 for color correction with respect to a predetermined range of the input image N in the same manner as the light and dark correction unit 12 described above performs on the image NA. A color difference value is calculated for the pixel. Specifically, absolute values s_R, s_G and s_B of color differences for each primary color of each pixel are obtained from color information values R, G and B for each primary color of each pixel using the following equation (3). However, in formula (3), abs represents an absolute value.
s_R = abs (RG), s_G = abs (GB), s_B = abs (BR) (3)
When all the absolute values s_R, s_G, s_B of the color differences obtained by the above equation (3) are less than or equal to the predetermined threshold Th_s, the color analysis unit 13 determines the original color information values R, G, Set B as it is. On the other hand, when any one of the obtained absolute values s_R, s_G, and s_B of the color difference exceeds the threshold Th_s, the color analysis unit 13 sets all the color information values of the pixel to 0, and R = G = Let B = 0. The value of the threshold Th_s is, for example, Th_s = 30.
The color analysis unit 13 corrects the color of the input image N by resetting the color information value for each pixel in the region R2 of the input image N by the processing described above, and the inside of the region R2 of the input image N A color-corrected image MB in which the colors are masked is created.
(Iv) Object detection unit 14
The object detection unit 14 creates an image for detecting the main mark included in the input image based on the light and dark correction image created by the light and dark correction unit 12 as follows.
FIG. 6 is a diagram for explaining an example of the operation of the object detection unit 14. In FIG. 6, the image NB on the left side shows an example of an image after light and dark correction, and the image ND on the right side shows an example of an image in which the present sign and the background are separated.
The object detection unit 14 is a weighted average obtained by weighting the average values aveR1 and aveR2 of the brightness of the color in the above-described image (N-1) and N calculated by the light and dark correction unit 12 using Equation (4) below. The value aveRN is calculated. In Equation (4), C2 / C1 represents a weighting coefficient for the past input image (N−1), and C3 / C1 represents a weighting coefficient for the current input image N. Further, C1 = C2 + C3.
aveRN = aveR1 * C2 / C1 + aveR2 * C3 / C1 (4)
In the above equation (4), when it is desired to make the weighted average value aveRN closer to the brightness of the color of the past input image (N−1), C2 is made larger than C3 and the past input image (N−1). The weight of can be increased. On the other hand, in order to make the weighted average value aveRN closer to the brightness of the color of the current input image N, C3 is made larger than C2 to increase the weight of the current input image N. However, if C3 is increased and the current input image N is emphasized too much, this sign may not be detected accurately in the subsequent processing. Therefore, the weight C2 is not set too small. It is also necessary to consider the image (N-1). For example, when increasing the weight of the past input image (N−1), C2 = 0.9 and C3 = 0.1 are set. In order to increase the weight of the current input image N, it is conceivable to set C2 = C3 = 0.5.
After calculating the weighted average value aveRN as described above, the object detection unit 14 next uses the following equation (5) to determine the threshold for separating the main mark to be detected from the contrast correction image NB and the background: Th is obtained for each image.
Th = aveRN + α (5)
Α in the above formula (5) is a correction value for setting the threshold Th from the weighted average value aveRN. By appropriately setting the value of the correction value α, it is possible to extract only pixels having a desired brightness or pixels having a desired brightness or less from the light and dark correction image NB. In other words, α in Expression (5) is a parameter for facilitating the extraction of the sign as the detection target object from the brightness correction image NB.
In the above equation (2), when the a value of each pixel in the area R2 of the image NA is cn, the brightness value cnCor of the color of each pixel of the light / dark correction image NB is the a value of each pixel of the image NA. It is set according to In this case, the object detection unit 14 obtains a threshold value Th for each image with α being a positive value in the equation (5), and the background and the present sign 31 are separated from the region R2 of the light and dark correction image NB using the threshold value Th. Create an image ND. Specifically, for each pixel in the region R2 of the brightness correction image NB, when cnCor ≧ Th, the brightness of the color after separation is set to an s value (for example, s = 255), and when cnCor <Th Sets the brightness of the color after separation to the t value (for example, t = 0). As a result, an object having a color brightness of a predetermined value or more in the region R2 can be efficiently separated as the main sign 31.
On the other hand, in the above equation (2), when the b value of each pixel in the region R2 of the image NA is cn, the brightness value cnCor of the color of each pixel of the light / dark correction image NB is the value of each pixel of the image NA. b Set according to the value. In this case, the object detection unit 14 obtains a threshold value Th for each image with α being a negative value in the equation (5), and using this threshold value Th, the background and the main sign 31 are separated from the region R2 of the light / dark correction image NB. Create an image ND. Specifically, for each pixel in the region R2 of the brightness correction image NB, when cnCor ≦ Th, the brightness of the color after separation is set to an s value (for example, s = 255), and when cnCor> Th Sets the brightness of the color after separation to the t value (for example, t = 0). As a result, an object whose color brightness is not more than a predetermined value in the region R2 can be efficiently separated as the main sign 31.
The object detection unit 14 compares the cnCor value with the threshold value Th for each pixel in the region R2 of the light and dark correction image NB by the processing described above, and sets the brightness of the separated color based on the comparison result. By doing this, a separated image ND is created by separating the main sign 31 that is the detection target object and the background from the light / dark correction image NB. The separated image ND includes many candidates of the marker 31.
In addition, the object detection unit 14 generates an image for detecting an auxiliary marker included in the input image based on the color correction image generated by the color analysis unit 13 as follows.
FIG. 7 is a diagram for explaining an example of the operation of the object detection unit 14. In FIG. 7, the image MB on the left side shows an example of an image after color correction, as in FIG.
The object detection unit 14 extracts a rectangular portion corresponding to the shape of the auxiliary marker in the region R2 of the color corrected image MB, thereby separating the auxiliary marker 32 as the detection target object from the color corrected image MB and the image MC Create The separated image MC includes many candidates for the auxiliary marker 32.
As described above, when the separated image ND corresponding to the main mark 31 and the separated image MC corresponding to the auxiliary mark 32 are created, the object detection unit 14 next detects an object to be detected separated from the background in these images. A process is performed to identify which of the main indicator 31 and the auxiliary indicator 32 corresponds to. In this process, for example, the object detection unit 14 reads from the image storage unit 90 a reference image set in advance corresponding to the label to be identified, and compares the reference image with the separated images ND and MC, respectively. It is determined whether the detection target object is the main marker 31 or the auxiliary marker 32. Specifically, for example, a histogram A of the reference image and a histogram B of the separation image ND (or MC) are created using the RGB values of the reference image and the separated image ND (or MC), respectively. Based on the shape or the Bhattacharyya distance, the similarity between the histograms A and B is calculated. Using this similarity, it is determined whether or not the main label 31 (or auxiliary label 32) is included in the separated image ND (or MC).
The similarity between the histograms A and B can be calculated using, for example, the following equation (6). In Expression (6), B32 (c) represents the Bhattacharyya distance between the histograms A and B. The similarity R can be calculated using B32 (r) for the r component of B32 (c), B32 (g) for the g component, and B32 (b) for the b component. Here, c represents any of r, g, and b. Also, HA (I) and HB (I) represent the frequency of gradation value I of histograms A and B, respectively, and HSUM represents the total number of bins of the histogram.
The object detection unit 14 calculates the degree of similarity between the histograms by the processing described above, and determines the degree of similarity between the reference image and the main marker 31 and the auxiliary marker 32 that are objects to be detected. As a result, it is possible to detect the main marker 31 and the auxiliary marker 32 from the separated images ND and MC using a preset reference image, respectively. Furthermore, for the similarity determination between histograms, a discriminator is created from the feature amount of the image by machine learning using a known neural network, and the discriminator is used to discriminate the detected object. Also good. That is, when a plurality of reference images determined to have a high degree of similarity are detected, a classifier using a neural network identifies which image is correct (probable) as a detected object.
(V) Object relation analysis unit 15
The object association analysis unit 15 analyzes the association between the main sign and the auxiliary sign detected from the separated images ND and MC by the object detection unit 14 as follows.
FIG. 8 is a diagram for explaining an example of the operation of the object relation analysis unit 15. In FIG. 8, the left image ND shows an example of an image in which the main sign and the background are separated, as in FIG. 6, and the right image MC shows an example of an image in which the auxiliary sign and the background are separated, as in FIG.
When the main label and the auxiliary label are associated on the basis of the separated image ND, the object relation analysis unit 15 first places the position directly below the main label 31 in the region R2 in the separated image ND, as shown in FIG. An area R3 is set, and this area R3 is set to the same position in the separated image MC. Then, it is determined whether or not the auxiliary marker 32 is present in the region R3 of the separated image MC. If the auxiliary marker 32 is present, the main marker 31 in the separated image ND and the auxiliary region 32 in the separated image MC are associated with each other.
FIG. 9 is a diagram for explaining an example of the operation of the object relation analysis unit 15. In FIG. 8, the left image MC shows an example of an image in which the auxiliary sign and the background are separated as in FIG. 7, and the right image ND shows an example of an image in which the sign and the background are separated as in FIG.
When the main label and the auxiliary label are associated on the basis of the separated image MC, as shown in FIG. 9, the object association analysis unit 15 first positions the position directly above the auxiliary label 32 in the region R2 in the separated image MC. The region R4 is set to the same position in the separated image ND. Then, it is determined whether or not the main marker 31 is present in the region R4 of the separated image ND. If so, the main marker 31 in the separated image ND and the auxiliary region 32 in the separated image MC are associated with each other.
The object association analysis unit 15 determines the association between the main marker 31 and the auxiliary marker 32 in the predetermined range below the main marker 31 or in the predetermined range above the auxiliary marker 32 by the processing as described above. R3 and R4 are set. Then, when the auxiliary marker 32 is present in the region R3 in the separated image MC, or when the main marker 31 is present in the region R4 in the separated image ND, the main marker 31 and the auxiliary marker 32 are associated with each other. The flag 31 is set to 1 in the object detection information indicating the detection results of the main label 31 and the auxiliary label 32 thus associated. On the other hand, for an object that has not been associated, 0 is set in the flag f in the object detection information.
A plurality of auxiliary markers 32 may be present directly below the marker 31. In such a case, the relevance between these objects can be analyzed by the same processing as described above. However, in order to associate these objects with each other, for example, the flag f is set to 2 in the object detection information of each object. Set. Thus, it is preferable to set a unique value in the object detection information flag of each object so that the combination of the objects can be known.
(Vi) Direction determination unit 16
The orientation determination unit 16 determines the orientation of these objects for the main sign and the auxiliary sign detected by the object detection unit 14. FIG. 10 is a diagram for explaining an example of the operation of the orientation determination unit 16.
The orientation determination unit 16 obtains the width w and the height h in the input image for each of the detected objects b1, b2, b3 and b4 as shown in FIG. Note that the objects b1, b2, b3, and b4 in FIG. 10 correspond to either the main sign or the auxiliary sign detected by the object detection unit 14, respectively. Next, a ratio ratio between the width w and the height h of each object is calculated using the following equation (7).
ratio = w / h (7)
If the calculated ratio ratio is equal to or greater than a predetermined threshold Th_m (for example, Th_m = 0.7), the direction determining unit 16 determines that the direction of the object is related to the traveling direction of the vehicle, and detects the object. In the information, the direction flag fm is set to 1. On the other hand, when the ratio ratio is less than the threshold Th_m, the direction determination unit determines that the direction of the object is not related to the traveling direction of the vehicle, and sets 0 in the direction flag fm in the object detection information. As a result, for example, in the example of FIG. 10, the flag fm for the objects b1 and b2 is set to 1 and the flag fm for the objects b3 and b4 is set to 0.
The direction determination unit 16 determines the direction of the main sign and the auxiliary sign based on the ratio of the width and height in the input image of the main sign and the auxiliary sign detected from the input image by the processing described above. can do. The threshold Th_m is preferably set to a different value depending on whether the detected object is a main sign or an auxiliary sign. Also, the orientation of the detected object can be determined without using the ratio ratio. For example, a rectangle surrounding the object detected in the input image may be obtained, the direction of the object may be determined from the inclination of each straight line of the rectangle, and the flag fm may be set.
(Vii) Reliability determination unit 17
The reliability determination unit 17 determines the reliability of the detection results of these objects for the main label and the auxiliary label detected by the object detection unit 14. FIG. 11 is a diagram for explaining an example of the operation of the reliability determination unit 17.
The reliability determination unit 17 obtains the position (latitude, longitude) of each object based on the detected position information of the vehicle at the time of shooting each object, the mounting position of the on-vehicle camera, the shooting direction, the angle of view, and the like. . Then, as shown in FIG. 11, the acquired position detection frequencies are accumulated for each object and stored in the storage device 203. At this time, the detection result of the image processing apparatus 1 owned by another user may be acquired and added to the accumulated result. As a result, multiple detection results are accumulated for each object, that is, each road sign.
When the accumulation result of the position acquired for each road sign is obtained as described above, the reliability determination unit 17 compares the accumulated detection frequency with a preset threshold value Th_h. As a result, if the detection frequency is equal to or higher than the threshold Th_h, it is determined that the reliability C with respect to the position (latitude, longitude) of the detected road sign is high. In this way, by determining the reliability of the position with respect to the detected road sign, the position of the road sign can be accurately obtained even when images taken by the in-vehicle cameras of various vehicles are used. That is, even if the moving speed and the imaging position are different for each moving object mounted with the on-vehicle camera, and therefore the position of the road sign detected is slightly different, the correct position can be recognized.
(Vi) Drawing unit 18
The drawing unit 18 draws the detection result of the main sign and the auxiliary sign by the object detection unit 14 on the input image based on the determination result of the reliability by the reliability determination unit 17. FIG. 12 is a diagram for explaining an example of the operation of the drawing unit 18. 5, an image N on the left side shows an example of an input image represented in the RGB color space as in FIG. 3, and an image NE on the right side shows an example of an image on which the detection results of the present sign and the auxiliary sign are drawn. .
When the reliability determination unit 17 determines that the reliability C is high, as shown in FIG. 12, the detection frames 34 and 35 surround the main marker 31 and the auxiliary marker 32 detected by the object detection unit 14 respectively. Is drawn on the input image N to create an image NE showing the detection results of these objects. On the other hand, when the detection frequency does not reach the threshold Th_h and the reliability determination unit 17 determines that the reliability C is low, the drawing unit 18 draws the detection frames 34 and 35 on the input image N. No image NE is created.
(Vii) Recording unit 19
The recording unit 19 stores the image NE created by drawing the detection frames 34 and 35 on the input image N in the drawing unit 18 in the image storage unit 90.
<Processing Procedure of Image Processing Device>
FIG. 13 is a flowchart for explaining the operation of the image processing apparatus 1 according to the first embodiment of the present invention.
(I) Step S1201
The input unit 10 receives an image input from the in-vehicle camera and outputs the input image N to the color space conversion unit 11.
(Ii) Step S1202
The color space conversion unit 11 obtains an image NA obtained by converting the input image N output from the input unit 10 into a Lab color space image.
(Iii) Step S1203
The brightness correction unit 12 calculates the average value aveR2 of the brightness of the colors in the region R2 from the image NA obtained by the color space conversion unit 11. In addition, the contrast correction unit 12 reads the image (N-1) A after the temporal color space conversion from the image storage unit 90, and calculates the average value aveR1 of the brightness of the colors in the region R1. . Then, the light / dark correction unit 12 generates an image NB with light and dark corrected using the above-described equations (1) and (2).
(Iv) Step S1204
The color analysis unit 13 determines the absolute value s_R, s_G, s_B of the color difference for each primary color of each pixel using the above equation (3), and compares these values with the threshold Th_s to mask the color. An image MB after color correction is made.
(V) Step S1205
The object detection unit 14 obtains the threshold value Th for each image using the above-described equations (4) and (5).
(Vi) Step S1206
The object detection unit 14 compares each pixel value cnCor of the image NB corrected for light and dark with a threshold Th. As a result, if cnCor corresponds to the value a, the process proceeds to step S1207 if cnCor ≧ threshold Th, and if cnCor <threshold Th, the process proceeds to step S1208. When cnCor corresponds to the b value, the direction of the inequality sign in the determination in step S1206 is opposite to that in FIG. That is, if cnCor ≦ threshold Th, the process proceeds to step S1207, and if cnCor> threshold Th, the process proceeds to step S1208.
(Vii) Step S1207
Even when each pixel value cnCor of the image NB corresponds to either the a value or the b value, the object detection unit 14 sets an s value (for example, 255) as the correction value.
(Viii) Step S1208
Even if each pixel value cnCor of the image NB corresponds to either the a value or the b value, the object detection unit 14 sets a t value (for example, 0) as the correction value.
(Ix) Step S1209
The object detection unit 14 repeats the processing from step S1206 to S1208 until correction values are obtained for all the pixels in the target image. By repeating the processing from step S1206 to S1209, an image ND in which the background and the object are separated from the image NB is created, and the main marker 31 that is the detection target object is detected.
(X) Step S1210
The object detection unit 14 obtains an object forming a rectangle from within the region R2 of the image MB. Thereby, the image MC in which the background and the object are separated from the image MB is created, and the auxiliary sign 32 that is the detection target object is detected.
(Xi) Step S1211
The object detection unit 14 reads a reference image from the image storage unit 90, creates a histogram for each of the detected object image and the reference image, and uses the above equation (6) to determine the similarity R between the histograms. calculate. Then, the degree of similarity between the detected object and the reference image is determined based on the calculated degree of similarity R, and it is determined that the degree of similarity is high when, for example, similarity R ≦ threshold Th_R, and the detected object is identified as a road sign To do. In addition, since the similarity R is calculated as the Bhattacharyya distance, the smaller the value of the similarity R, the shorter the distance between the histograms, which means that the similarity is higher. At this time, as described above, a discriminator obtained by machine learning using a neural network may be used, and the discrimination result by the discriminator may be added to the above determination to determine whether or not the marker is to be identified.
(Xii) Step S1212
The object association analysis unit 15 sets a detection region above or below the object detected by the object detection unit 14 and analyzes the relationship between the objects. That is, when the object is the main sign, a detection area is set immediately below the object, and it is analyzed whether or not the auxiliary sign object exists. When the object is an auxiliary sign, a detection region is set immediately above the object, and it is analyzed whether or not the sign is present. As a result, when each target object exists, the flag f of each object is set to 1, and when it does not exist, 0 is set to the flag f of each object. Note that a unique value is set in the flag of each object so that the combination of the objects can be known.
(Xiii) Step S1213
The direction determination unit 16 calculates a ratio ratio for each object detected using Expression (7), and determines the direction of the object. That is, when the ratio ratio is equal to or greater than the threshold Th_m, it is determined that the detected object direction is related to the traveling direction of the vehicle, and 1 is set to the direction flag fm. On the other hand, if the ratio ratio is less than the threshold Th_m, it is determined that the detected object orientation is not related to the traveling direction of the vehicle, and 0 is set to the orientation flag fm.
(Xiv) Step S1214
The reliability determination unit 17 accumulates position information (latitude, longitude) at the time of shooting of the detected object, and determines that the reliability C with respect to the position of the detected object is high if the accumulated detection frequency is equal to or higher than the threshold Th_h. To do. On the other hand, if the detection frequency is less than the threshold Th_h, it is determined that the reliability C is low. The reliability determination unit 17 determines the reliability C for each object detected by the object detection unit 14.
(Xv) Step S1215
When the degree of reliability C is high, the drawing unit 18 draws the detection frames 34 and 35 on the input image N so as to surround the object detected by the object detection unit 14 and creates an image NE. On the other hand, when the reliability C is low, the drawing unit 18 does not draw the detection frame on the input image N.
(Xvi) Step S1216
The recording unit 19 stores the image NE in which the detection frames 34 and 35 are drawn by the drawing unit 18 in the image storage unit 90.
As described above, according to the first embodiment of the present invention, the average value aveR1 of color brightness based on the past input image (N-1) and the color brightness based on the current input image N An image NB is generated by correcting the brightness and darkness of the input image N using the average value aveR2 of and the image ND is created by obtaining a threshold Th for separating the sign and the background for each image NB. . Therefore, it is possible to separate the background in the input image N from the sign that is the detection target object using the threshold Th.
For the primary colors R, G, and B, the absolute values s_R, s_G, and s_B of the color differences for each primary color of each pixel in the input image N are calculated, and an image MB masking the colors is created. An image MC is created by obtaining a rectangle in the image MB. Accordingly, it is possible to separate the background in the input image N and the auxiliary sign that is the detection target object.
In addition, the relationship is analyzed by setting regions above and below the detected object and analyzing the presence or absence of the object in the region. Therefore, it becomes possible to determine the relationship between objects.
Further, the direction is obtained from the ratio of the width and height of the detected object. Therefore, it is possible to determine whether the detected direction of the object is a direction related to the traveling direction of the vehicle.
Further, by accumulating the position information of the detected objects and determining the detection frequency, the position information of each detected object can be obtained more accurately.
In addition, since an object is detected from within the image MB in which the color is masked and the image NB in which the contrast is emphasized, the color of the object reflected in the image even if part of the main mark or auxiliary mark in the image is cut. Since the object is detected according to the brightness and darkness, it is possible to detect the main sign and the auxiliary sign.
In this way, an image in which the contrast of the target image is emphasized is created using the brightness information of the past image and the target image, and the threshold value for separating the area in the image is determined for each image, depending on the traveling direction of the moving vehicle. Even when the brightness of the image in the video changes, it is possible to detect the object in the background by separating the background in the image from the object in the background. In addition to more accurate position information, it is possible to detect an object from the image and determine the relationship between the detected objects and the direction of the object. Furthermore, by detecting an object from the image of an in-vehicle smartphone taken by a large number of unspecified users and obtaining a more accurate position from the detection frequency of position information, it can be used on newly established roads or roads that have changed due to construction. It is possible to timely detect the road appendages of
According to the 1st Embodiment of this invention demonstrated above, there exist the following effects.
(1) The image processing apparatus 1 includes a light / dark correction unit 12, a color analysis unit 13, an object detection unit 14, and an object related analysis unit 15. The light / dark correction unit 11 creates a light / dark correction image NB obtained by correcting the light / dark of the input image N photographed by a vehicle-mounted camera mounted on the vehicle. The color analysis unit 13 creates a color correction image MB in which the color of the input image N is corrected. The object detection unit 14 detects the main marker 31 included in the input image N based on the light and dark correction image NB, and detects the auxiliary marker 32 included in the input image N based on the color correction image MB. The object relation analysis unit 15 associates the main marker 31 and the auxiliary marker 32 with each other based on the positional relationship between the main marker 31 and the auxiliary marker 32 detected by the object detection unit 14 in the input image N. A road sign combining 31 and the auxiliary sign 32 is recognized. Since it did in this way, the road sign which combined this sign and the auxiliary sign can be recognized correctly.
(2) The image processing apparatus 1 further includes the orientation determination unit 16. The orientation determination unit 16 determines the orientation of the main marker 31 and the auxiliary marker 32 based on the ratio ratio of the width w and height h in the input image N of the detected main marker 31 and auxiliary marker 32. Since it did in this way, it can be determined whether the recognized road sign shows the road regulation etc. with respect to the advancing direction of a vehicle.
(3) The image processing apparatus 1 further includes the reliability determination unit 17. The reliability determination unit 17 acquires the position of the road sign, and determines the reliability C of the road sign based on the accumulated result of the acquired position of the road sign. Since it did in this way, it can be determined whether the detection result of a road sign is correct.
(4) The light / dark correction unit 12 sets the target region R2 in a predetermined range of the input image N, and within the region R1 corresponding to the target region R2 of the past image (N−1) photographed before the input image N. The light and dark correction image NB is created on the basis of the average value aveR1 of the color brightness and the average value aveR2 of the color brightness in the target region R2 of the input image N. Since it did in this way, the brightness-and-darkness correction | amendment image NB suitable for detecting this label | marker 31 can be produced.
(5) The color analysis unit 13 sets the target area R2 in a predetermined range of the input image N, and creates the color correction image MB based on the color difference values s_R, s_G, s_B in the target area R2 of the input image N. To do. Since it did in this way, the color correction image MB suitable for detecting the auxiliary | assistant label | marker 32 can be produced.
(6) The object detection unit 14 detects the main sign 31 and the auxiliary sign 32 using a preset reference image. As a result, the present label 31 and the auxiliary label 32 can be accurately detected.
(7) When the auxiliary sign 32 exists in the area R3 set in the predetermined range below the sign 31, or in the area R4 set in the predetermined range above the auxiliary sign 32, the object-related analysis unit 15 When the present label 31 is present, the present label 31 and the auxiliary label 32 are associated with each other. Since it did in this way, this sign 31 and auxiliary sign 32 which constitute the same road sign can be related correctly and certainly.
FIG. 14 is a block diagram showing a configuration of a warning device 1300 according to the second embodiment of the present invention. The warning device 1300 is used by being mounted on a vehicle, and functions as a navigation system that displays a route on a map and guides the user to a destination, for example. Further, information on objects such as road signs around the vehicle is collected in real time, and a warning (alert) is output by screen display or sound when approaching a predetermined warning location. The warning place may be a predetermined place such as a general office such as a government office or a police station, or a landmark building, or a place marked by the user while the vehicle has been driven in the past. Also good. The warning device 1300 according to the present embodiment provides useful information for the user while collecting information from the user.
The warning device 1300 includes an imaging device 1301 that captures image data, an image processing device 1 that recognizes an image including a detection target from the image data, and a display device 1302 that displays a recognized image output from the image processing device 1. And an output device 1303 that outputs alert information output from the image processing apparatus 1. For example, a device such as a smart phone can be used as the warning device 1300. The imaging device 1301 is configured by a CMOS sensor, a CCD camera, or the like, and corresponds to the in-vehicle camera described in the first embodiment. The configuration and operation of the image processing apparatus 1 are as described in the first embodiment.
As described in the first embodiment, the image processing apparatus 1 recognizes various road signs including the main sign and the auxiliary sign from the image captured by the imaging device 1301. Furthermore, a reference image corresponding to an object such as an appendage on the road may be prepared and included in the recognition target.
The display device 1302 displays an image indicating a recognition result of a velocity sign, an auxiliary sign, and the like output from the image processing apparatus 1 and corresponds to, for example, a display device of a smartphone.
The output device 1303 outputs a warning based on the alert information output from the image processing apparatus 1 as an image or a sound, and corresponds to, for example, a display device or a speaker of a smartphone.
The warning device 1300 outputs alert information from the image processing device 1 to the output device 1303 based on the recognition result of an object such as a road sign by the above-mentioned object relation analysis unit 15 in the image processing device 1. When the alert information is output from the image processing apparatus 1, the output device 1303 outputs a warning to the user who is the driver of the vehicle based on the alert information. For example, if the content of the detected object matches the map information, the map information is notified to the user. Further, if the detected object content and the map information do not match in one detection, the alert information is not notified to the user at that time. In addition, if the object could not be detected multiple times at the same point, but there is object information in the map information, the sign at that point may have changed, so a message is sent to prompt the user to confirm the sign To do. For example, message notification is performed by outputting a voice "Please check the sign." In addition, when notifying the road sign which combined this mark and the auxiliary sign, you may notify a user combining these information, and you may divide these information and notify a user. Furthermore, a photographed image at a point where an alert is issued, an image indicating a recognition result of an object, or the like may be registered in the warning device 1300 together with information indicating the point.
According to the second embodiment of the present invention described above, the warning device 1300 outputs a warning to the driver of the vehicle based on the recognition result of the road sign by the image processing device 1 and the object relation analysis unit 15 An output device 1303 as an output unit. As a result, a road sign such as a speed sign combining this sign and an auxiliary sign is recognized from an image taken with a smart phone or the like mounted on the vehicle, and an image indicating the recognition result and alert information are set as a set to the user. It is possible to provide a warning device 1300 for notification.
FIG. 15 is a block diagram showing a configuration of an image processing system 1400 according to the third embodiment of the present invention. The image processing system 1400 creates point of interest (POI) information from an image captured by a vehicle, and includes a server 1403 and a mobile terminal device 1407.
The mobile terminal device 1407 includes an imaging device 1401 that captures image data, an image processing device 1A that simply detects an image including a detection target from the image data, and a post-detection image output from the image processing device 1A. And a communication device 1402 for receiving the recognized image transmitted from the server 1403 and a display device 1405 for displaying the recognized image. As the mobile terminal device 1407, for example, a device such as a smartphone can be used in the same manner as the warning device 1300 described in the second embodiment. The imaging device 1401 is configured by a CMOS sensor, a CCD camera, or the like, and corresponds to the in-vehicle camera described in the first embodiment.
The image processing apparatus 1A has a functional configuration from the input unit 10 to the object detection unit 14 among the functional configurations of the image processing apparatus 1 described in FIG. 1 in the first embodiment. That is, the mobile terminal device 1407 has an input unit 10, a color space conversion unit 11, a light and dark correction unit 12, a color analysis unit 13 and an object detection unit 14 as the image processing apparatus 1A. In the image processing apparatus 1 </ b> A, the object detection unit 14 detects main signs, auxiliary signs, and the like from the images captured by the imaging device 1401, and outputs images indicating these detection results to the communication device 1402 as post-detection images. Furthermore, the image processing apparatus 1 </ b> A may include objects such as road accessories, a specific signboard representing facility information, spot information, and the like as detection targets. The post-detection image may be the entire captured image or a partial image including the detected object. The communication device 1402 transmits post-detection images for these detection target objects output from the image processing apparatus 1A to the server 1403, and corresponds to the communication device 206 described in FIG. 2 in the first embodiment.
The server 1403 receives the detected image transmitted from the mobile terminal 1407 and the communication device 1404 for transmitting the recognized image output from the image processing apparatus 1B to the mobile terminal 1407, and receives the received image after the detection The image processing apparatus 1B recognizes various road signs composed of signs and auxiliary signs, and a storage device 1406 that stores POI information based on the recognized image output from the image processing apparatus 1B.
The image processing apparatus 1B has the same functional configuration as the image processing apparatus 1 described in FIG. 1 in the first embodiment. The image processing apparatus 1B uses the post-detection image transmitted from the mobile terminal device 1407 by the input unit 10 to the object relation analysis unit 15 to detect a road sign composed of this sign and an auxiliary sign, an on-road accessory, Recognize objects such as signs. In the storage device 1406, these post-recognition images are combined with the position information and stored as POI information.
The communication device 1404 transmits post-recognition images for these recognition target objects output from the image processing apparatus 1B to the mobile terminal apparatus 1407, and corresponds to the communication device 206 described in FIG. 2 in the first embodiment. To do.
When a recognized image is transmitted from the server 1403, the communication device 1402 of the mobile terminal device 1407 receives this and outputs it to the display device 1405. The display device 1405 displays the post-recognition image transmitted from the server 1403, and corresponds to, for example, a smartphone display device. At this time, the display device 1405 displays, for example, a map screen, and displays a mark indicating the presence of an object included in the image after recognition at a corresponding position on the map screen, thereby notifying of the recognized road sign etc. May be notified to the user who is the driver of the vehicle.
According to the third embodiment of the present invention described above, the image processing system 1400 has the mobile terminal device 1407 mounted on the vehicle, and the server 1403 that communicates with the mobile terminal device 1407. The mobile terminal device 1407 includes a light / dark correction unit 12, a color analysis unit 13 and an object detection unit 14 as the image processing apparatus 1A, and an image after detection showing the detection result of the main marker and the auxiliary marker by the object detection unit 14 And a communication device 1402 as an image transmission unit for transmitting the image data to the server 1403. The server 1403 includes a communication device 1404 as an image receiving unit for receiving an after-detection image transmitted from the mobile terminal device 1407, and the image processing apparatus 1B uses the after-detection image received to provide a sign and an assistance A configuration equivalent to the image processing apparatus 1 described with reference to FIG. 1 is provided, which recognizes a road sign combined with a sign. As a result, a road sign or a specific sign that combines this sign and an auxiliary sign is recognized from an image taken with a smart phone or the like mounted on the vehicle, and the recognized image and position information are stored as POI information as a set. A system can be provided.
In the image processing system 1400, the communication device 1404 of the server 1403 also functions as a second image transmission unit that transmits the recognized image regarding the road sign recognized by the image processing apparatus 1B to the mobile terminal apparatus 1407. In addition, the communication device 1402 of the mobile terminal device 1407 also functions as a second image receiving unit that receives the recognized image transmitted from the server 1403. Furthermore, the mobile terminal device 1407 includes a display device 1405 as a notification unit that notifies the driver of the vehicle of a road sign based on the image after recognition received by the communication device 1402. Since this is done, it is possible to notify the driver of useful information when driving the vehicle.
FIG. 16 is a block diagram showing a configuration of an image processing system 1500 according to the fourth embodiment of the present invention. The image processing system 1500 outputs a warning to the driver of the vehicle based on an image captured by the vehicle, and includes a server 1503 and a mobile terminal device 1508.
Similar to the warning device 1300 described in the second embodiment, the image processing system 1500 functions as a navigation system that displays a route on a map, for example, and guides the user to a destination. Furthermore, information of an object such as a road sign present around the vehicle is collected in real time, and a warning (alert) is output by screen display or voice when approaching a predetermined warning place. The warning location may be a predetermined location such as a general-purpose building such as a government office or a police station, or a landmark-like building, or a location marked by a user while driving a vehicle in the past. Also good. The image processing system 1500 according to the present embodiment provides information useful to the user while collecting information from the user.
The mobile terminal device 1508 includes an imaging device 1501 for capturing image data, an image processing device 1A for simply detecting an image including a detection target from the image data, and a server 1503 a detected image output from the image processing device 1A. And a display device 1505 for displaying the image after recognition, and an output device 1506 for outputting the alert information. Yes. Similar to the mobile terminal device 1407 described in the third embodiment, for example, a device such as a smartphone can be used as the mobile terminal device 1508. The imaging device 1501 is configured by a CMOS sensor, a CCD camera, or the like, and corresponds to the in-vehicle camera described in the first embodiment.
The configuration and operation of the image processing apparatus 1A are as described in the third embodiment. The communication device 1502 corresponds to the communication device 206 described in FIG. 2 in the first embodiment.
The server 1503 receives the post-detection image transmitted from the mobile terminal device 1508, and transmits the post-recognition image and alert information output from the image processing device 1B to the mobile terminal device 1508, and the received post-detection It has an image processing device 1B that recognizes various road signs composed of main marks and auxiliary marks from images, and a storage device 1507 that stores recognition information based on the image after recognition output from the image processing device 1B. ing.
The configuration and operation of the image processing apparatus 1B are as described in the third embodiment. The server 1503 outputs the image after recognition and alert information to the communication device 1504 from the image processing apparatus 1B based on the recognition result of the object such as the road sign by the image processing apparatus 1B. In the storage device 1507, a post-recognition image obtained by the image processing apparatus 1B recognizing road appendages such as road signs is combined with position information and stored as recognition information. The communication device 1504 transmits the image after recognition and the alert information on the recognition target object output from the image processing apparatus 1B to the mobile terminal device 1508, and the communication device 206 described in FIG. 2 in the first embodiment is used. Equivalent to.
When the image or alert information after recognition is transmitted from the server 1503, the communication device 1502 of the mobile terminal 1508 receives them and outputs them to the display device 1505 and the output device 1506. Similar to the display device 1405 described in the third embodiment, the display device 1505 displays the image after recognition transmitted from the server 1503 to notify the user, and corresponds to, for example, a display device of a smartphone. .
The output device 1506 outputs an alert based on the alert information transmitted from the server 1503 as an image or a sound, and corresponds to, for example, a display device or a speaker of a smartphone. Note that the server 1503 and the mobile terminal device 1508 may register the captured image at the point where the alert is issued, the image indicating the recognition result of the object, and the like together with the information indicating the point.
According to the fourth embodiment of the present invention described above, the image processing system 1500 is similar to the image processing system 1400 according to the third embodiment, and the mobile terminal device 1508 mounted on the vehicle and the mobile terminal device. And a server 1503 that communicates with the server 1508. The mobile terminal device 1508 includes, as the image processing apparatus 1A, a light / dark correction unit 12, a color analysis unit 13, and an object detection unit 14, and also includes a post-detection image that indicates a detection result of the main sign and the auxiliary sign by the object detection unit 14. And a communication device 1502 as an image transmission unit for transmitting the image data to the server 1503. The server 1503 includes a communication device 1504 as an image receiving unit for receiving an after-detection image transmitted from the mobile terminal device 1508, and the image processing apparatus 1B uses the after-detection image received to provide a main sign and assistance A configuration equivalent to that of the image processing apparatus 1 described with reference to FIG. 1 is provided, which recognizes a road sign combined with a sign. Further, in the image processing system 1500, the communication device 1504 of the server 1503 also functions as a warning information transmission unit that transmits warning information (alert information) based on the recognition result of the road sign by the image processing apparatus 1B to the mobile terminal device 1508. . In addition, the communication device 1502 of the mobile terminal device 1508 also functions as a warning information reception unit that receives warning information (alert information) transmitted from the server 1503. Furthermore, the mobile terminal device 1508 includes an output device 1506 as a warning output unit that outputs a warning to the driver of the vehicle based on the warning information (alert information) received by the communication device 1502. Accordingly, it is possible to provide a system for recognizing a road sign combining this sign and an auxiliary sign from an image photographed with a smart phone or the like mounted on the vehicle, and giving a warning based on the recognition result to the user. .
FIG. 17 is a block diagram showing a configuration of an image processing system 1600 according to the fifth embodiment of the present invention. For example, when a travel route is set by the user, image processing system 1600 presents the user with information on an object such as a road sign present around the vehicle in real time, and presents the user with the vehicle according to the travel route. Guide to. At this time, instead of displaying a route on a map and performing vehicle guidance as in the warning device 1300 described in the second embodiment, in this embodiment, a road sign related to vehicle guidance is set on a set route. Once recognized, the vehicle is guided based on the recognition result of the road sign. For example, when a road sign indicating a left turn direction is recognized at a point where a left turn is to be made, the vehicle is guided by a method such as outputting a voice “This is a left turn”. The image processing system 1600 has a server 1603 and a mobile terminal 1608.
The mobile terminal device 1608 includes an imaging device 1601 that captures image data, an image processing device 1A that simply detects an image including a detection target from the image data, and a post-detection image output from the image processing device 1A. And a display device 1605 for displaying the image after recognition, and an output device 1606 for outputting the guidance information. Yes. Similar to the mobile terminal 1407 described in the third embodiment and the mobile terminal 1508 described in the fourth embodiment, the mobile terminal 1608 can use, for example, a device such as a smart phone. The imaging device 1601 is configured by a CMOS sensor, a CCD camera, or the like, and corresponds to the in-vehicle camera described in the first embodiment.
The configuration and operation of the image processing apparatus 1A are as described in the third embodiment. The communication device 1602 corresponds to the communication device 206 described with reference to FIG. 2 in the first embodiment.
The server 1603 receives the detected image transmitted from the mobile terminal 1608, and the communication device 1604 for transmitting the recognized image and guidance information output from the image processing apparatus 1B to the mobile terminal 1608, and the received detection An image processing apparatus 1B that recognizes various road signs and direction signs made up of main signs and auxiliary signs from an image; and a storage device 1607 that stores recognition information based on the image after recognition output from the image processing apparatus 1B. have.
The configuration and operation of the image processing apparatus 1B are as described in the third embodiment. The server 1603 outputs the image after recognition and guidance information to the communication device 1604 from the image processing apparatus 1B based on the result of recognition of an object such as a road sign or a direction signboard by the image processing apparatus 1B. For example, it is identified whether or not the signboard is a direction signboard related to the traveling direction of the vehicle, and the guidance information is output from the arrow or letter of the direction signboard by identifying the direction of the arrow or letter by pattern matching or the like. In the storage device 1607, the image after recognition obtained by the image processing apparatus 1B recognizing road appendages such as road signs is combined with position information and stored as recognition information. The communication device 1604 transmits the image after recognition and guidance information for the recognition target object output from the image processing apparatus 1B to the mobile terminal device 1608, and the communication device 206 described in FIG. 2 in the first embodiment is used. Equivalent to.
When the image and guidance information after recognition are transmitted from the server 1603, the communication device 1602 of the mobile terminal 1608 receives these and outputs them to the display device 1605 and the output device 1606 respectively. Similar to the display device 1405 described in the third embodiment, the display device 1605 displays the image after recognition transmitted from the server 1603 to notify the user, and corresponds to, for example, a display device of a smartphone. .
The output device 1606 guides the vehicle to the destination by, for example, instructing the user with a picture or voice the direction in which the vehicle should turn, based on the guidance information transmitted from the server 1603. The output device 1606 corresponds to, for example, a display device or a speaker of a smartphone.
According to the fifth embodiment of the present invention described above, the image processing system 1600 is similar to the image processing system 1400 according to the third embodiment in that the mobile terminal device 1608 mounted on the vehicle and the mobile terminal device are And a server 1603 that communicates with 1608. The mobile terminal device 1608 includes, as the image processing device 1A, a light / dark correction unit 12, a color analysis unit 13, and an object detection unit 14, and a post-detection image indicating the detection result of the main sign and the auxiliary sign by the object detection unit 14. Is transmitted to the server 1603 as a communication device 1602 as an image transmission unit. The server 1603 includes a communication device 1604 as an image receiving unit that receives a post-detection image transmitted from the mobile terminal device 1608, and the image processing device 1B uses the received post-detection image to support the sign and the auxiliary device. A configuration equivalent to the image processing apparatus 1 described with reference to FIG. 1 is provided, which recognizes a road sign combined with a sign. Further, in the image processing system 1600, the communication device 1604 of the server 1603 transmits, to the mobile terminal device 1608, guidance information for guiding the vehicle to a predetermined destination based on the recognition result of the road sign by the image processing device 1B. It also functions as a guidance information transmission unit. In addition, the communication device 1602 of the mobile terminal device 1608 also functions as a guide information receiving unit that receives the guide information transmitted from the server 1603. Furthermore, the mobile terminal device 1608 includes an output device 1606 as a vehicle guidance unit that guides the vehicle to the destination based on the guidance information received by the communication device 1602. Accordingly, it is possible to provide a system for recognizing a road sign that is a combination of this sign and an auxiliary sign from an image photographed with a smart phone or the like mounted on the vehicle and simply guiding the vehicle based on the recognition result. It becomes possible.
The following modifications can be made to each embodiment described above.
In the color space conversion unit 11, an image obtained by converting the input image into the Lab color space is created, but it may be converted into an image in another color space such as the HSV color space. Even in that case, the same effect as the above-described embodiment is obtained.
Although the object detection unit 14 determines the similarity between the reference image and the image of the detected object using Equation (6), one of B32 (r), B32 (g), and B32 (b) May be used, and each combination may be used to determine the degree of similarity. Even in that case, the same effect as the above-described embodiment is obtained.
The object-related analysis unit 15 sets an area at a position directly below the main sign or a position just above the auxiliary sign and associates the main sign with the auxiliary sign. An area may be set at the left position or the right position of the auxiliary marker, or an area for searching for the marker or auxiliary marker may be set according to the positional relationship of the marker different for each country. Even in that case, the same effect as the above-described embodiment is obtained.
Although the orientation determination unit 16 determines the orientation of the object using the ratio of the width and height of the detected object using Equation (7), a rectangle including the object is determined, and the slope of each straight line of the rectangle determines the object May be determined. Even in that case, the same effect as the above-described embodiment is obtained.
The present invention can also be realized by a program code of software that realizes the functions of the embodiment. In this case, a storage medium storing the program code is provided to the system or apparatus, and a computer (CPU, MPU or the like) mounted on the system or apparatus reads the program code stored in the storage medium. In this case, the program code read out from the storage medium is executed by the computer to realize the functions of the above-described embodiment, and the program code, the storage medium storing the program code, and the program code A computer to be executed is a component of the present invention. As a storage medium for supplying such program code, for example, a flexible disk, CD-ROM, DVD-ROM, hard disk, optical disk, magneto-optical disk, CD-R, magnetic tape, nonvolatile memory card, ROM Etc. are used.
The embodiment and various modifications described above are merely examples, and the present invention is not limited to these contents as long as the features of the invention are not impaired. The present invention is not limited to the above-described embodiments and modifications, and various modifications can be made without departing from the spirit of the present invention.
DESCRIPTION OF SYMBOLS 1,1A, 1B ... Image processing apparatus 10 ... Input part 11 ... Color space conversion part 12 ... Brightness correction part 13 ... Color analysis part 14 ... Object detection part 15 ... Object-related analysis unit 16 ... orientation determination unit 17 ... reliability determination unit 18 ... drawing unit 19 ... recording unit 90 ... image storage unit 91 ... control unit 1300 ... warning device 1400, 1500, 1600... Image processing system
A light / dark correction unit that creates a light / dark correction image that corrects the light / dark of the input image captured by the vehicle-mounted camera mounted on the vehicle;
A color analysis unit that generates a color correction image in which the color of the input image is corrected;
An object detection unit that detects a main sign included in the input image based on the brightness correction image, and detects an auxiliary sign included in the input image based on the color correction image;
The main sign and the auxiliary sign are combined by associating the main sign and the auxiliary sign with each other based on the positional relationship in the input image of the main sign and the auxiliary sign detected by the object detection unit. An object-related analysis unit that recognizes road signs,
Wherein the position of the road sign to get the, based on the cumulative result of the position of the road sign acquired, an image processing apparatus and a reliability determination unit determines the reliability of the road signs.
The brightness correction unit sets a target region in a predetermined range of the input image, and an average value of brightness of colors in a region corresponding to the target region of a past image captured before the input image; An image processing apparatus that creates the brightness-corrected image based on an average value of brightness of colors in the target area of the input image.
The image processing apparatus, wherein the color analysis unit sets a target area in a predetermined range of the input image, and creates the color correction image based on a color difference value in the target area of the input image.
Target regions are respectively set in predetermined ranges of the input image and the contrast correction image, and an average value of brightness of colors in a region corresponding to the target region of a past image taken before the input image; A threshold value is set based on a weighted average value obtained by weighted averaging each of the brightness values of the colors in the target area of the input image with a predetermined weight, and using the threshold value, the first light and dark correction image Create a separate image of
A rectangular portion corresponding to the auxiliary sign is extracted from the color correction image to create a second separated image,
An image processing apparatus that detects the main mark and the auxiliary mark by respectively comparing a reference image set in advance with the first separated image and the second separated image .
The image processing apparatus according to any one of claims 1 to 4 .
The image processing apparatus further comprising an orientation determination unit that determines the orientations of the main label and the auxiliary label based on the ratio of the width and height in the input image of the main label and the auxiliary label.
The image processing apparatus according to any one of claims 1 to 5 .
The object-related analysis unit, when the auxiliary sign is present in an area set in an arbitrary predetermined range of the main sign according to a preset positional relationship between the main sign and the auxiliary sign, or the auxiliary sign An image processing apparatus for associating the main sign and the auxiliary sign with each other when the main sign is present in an area set in an arbitrary predetermined range.
An image processing apparatus according to any one of claims 1 to 6 .
A warning device comprising: a warning output unit that outputs a warning to the driver of the vehicle based on a recognition result of the road sign by the image processing device.
A terminal device mounted on a vehicle, and a server device that communicates with the terminal device;
An image transmission unit that transmits a post-detection image indicating a detection result of the main sign and the auxiliary sign by the object detection unit to the server device;
An image receiving unit that receives the detected image transmitted from the terminal device;
A second light / dark correction unit for creating a light / dark correction image obtained by correcting light / dark of the detected image received by the image receiving unit;
A second color analysis unit that creates a color-corrected image obtained by correcting the color of the post-detection image received by the image receiving unit;
A second object detection unit that detects a main mark included in the post-detection image based on the light and dark correction image, and detects an auxiliary mark included in the post-detection image based on the color correction image;
Based on the positional relationship between the main sign and the auxiliary sign in the post-detection image received by the image receiving unit, the main sign and the auxiliary sign are associated with each other, thereby And an object relation analysis unit that recognizes a road sign combined with the above.
The image processing system according to claim 8 .
The server device further includes a second image transmission unit that transmits a post-recognition image related to the road sign recognized by the object-related analysis unit to the terminal device,
A second image receiving unit that receives the post-recognition image transmitted from the server device;
An image processing system further comprising: a notification unit configured to notify a driver of the vehicle of the road sign based on the post-recognition image received by the second image reception unit.
The server device further includes a warning information transmission unit that transmits warning information based on a recognition result of the road sign by the object-related analysis unit to the terminal device,
A warning information receiving unit that receives the warning information transmitted from the server device;
An image processing system further comprising: a warning output unit that outputs a warning to the driver of the vehicle based on the warning information received by the warning information receiving unit.
The server device further includes a guidance information transmission unit that transmits guidance information for guiding the vehicle to a predetermined destination based on a recognition result of the road sign by the object-related analysis unit, to the terminal device,
A guidance information receiving unit that receives the guidance information transmitted from the server device;
An image processing system further comprising: a vehicle guidance unit that guides the vehicle to the destination based on the guidance information received by the guidance information reception unit.
A method of processing an input image captured by a vehicle-mounted camera mounted on a vehicle and input to a computer,
Setting a target area in a predetermined range of the input image;
Based on the average value of the brightness of the colors in the area corresponding to the target area of the past image taken prior to the input image and the average value of the brightness of the colors in the target area of the input image Te, it creates a brightness corrected image obtained by correcting the brightness of the input image,
Based on the color difference value in the target area of the input image, create a color correction image by correcting the color of the input image,
Detecting the main mark included in the input image based on the light and dark correction image;
Detecting an auxiliary marker included in the input image based on the color correction image;
A road sign combining the main sign and the auxiliary sign is obtained by associating the main sign and the auxiliary sign with each other based on the positional relationship of the detected main sign and the auxiliary sign in the input image. Recognizing image processing method.
JP2016026926A 2016-02-16 2016-02-16 Image processing device, warning device, image processing system, and image processing method Active JP6552979B2 (en)
JP2016026926A JP6552979B2 (en) 2016-02-16 2016-02-16 Image processing device, warning device, image processing system, and image processing method
US15/409,325 US10303960B2 (en) 2016-02-16 2017-01-18 Image processing device, alarming apparatus, image processing system, and image processing method
EP17151954.9A EP3208740A1 (en) 2016-02-16 2017-01-18 Image processing device, alarming apparatus, image processing system, and image processing method
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JP2016026926A Active JP6552979B2 (en) 2016-02-16 2016-02-16 Image processing device, warning device, image processing system, and image processing method
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