Patent Publication Number: US-2019197738-A1

Title: Image processing device, image processing system, recording medium and label

Description:
TECHNICAL FIELD 
     This disclosure relates to an image processing device, an image processing system, an image processing program, and a label. 
     The present application claims priority on the basis of Japanese Patent Application No. 2016-170638 filed on Sep. 1, 2016, and all the contents described in the above-mentioned Patent Application are incorporated for reference. 
     BACKGROUND ART 
     Conventionally, forklifts have been used for cargo handling in facilities, such as warehouses, factories or airports. Patent Document 1 discloses a person detection system for construction machines to detect persons being present around vehicle-type construction machines. According to Patent Document 1, an image taken by a camera installed on a shovel serving as a vehicle-type construction machine is used to detect a person being present around the shovel. More specifically, according to Patent Document 1, an HOG (Histograms of Oriented Gradients) feature amount is extracted from the image, and the candidate area of the person is identified from the extracted HOG feature amount. Furthermore, after the image of the candidate area of the person is converted into an image as viewed just from the front, the area of the helmet is extracted using the luminance gradient or the like of the pixels included in the image. 
     Furthermore, Patent Document 2 discloses a safety device for a forklift to detect a person being present around the forklift. Shapes being mutually different are drawn with a predetermined color on the forklift and a person, and the forklift and the person are imaged by a fixed camera having been preliminarily installed on the ceiling. The safety device extracts the above-mentioned shapes from the obtained image and detects the forklift and the person; in the case that the forklift and the person approach each other within a certain distance, the safety device issues a warning. 
     PRIOR ART DOCUMENT 
     Patent Document 
     Patent Document 1: International Publication No. WO 2015/186570 
     Patent Document 2: Japanese Patent Application Laid-Open Publication No. H09-169500 
     SUMMARY OF THE INVENTION 
     (1) An image processing device according to this disclosure is equipped with an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine; a judgement section for performing judgment processing as to whether predetermined two or more color areas having a predetermined positional relationship are included in the image taken by the image acquisition section; and a notification section for performing notification processing depending on the result of the judgment processing of the judgement section. 
     (8) An image processing system according to this disclosure is equipped with a label, which is placed on an object to be detected and on which predetermined two or more color areas are disposed in a predetermined positional relationship, and an image processing device for detecting the object to be detected, wherein the image processing device has an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine; a judgement section for performing judgment processing as to whether the predetermined two or more color areas are included in the image taken by the image acquisition section; and a notification section for giving a notification depending on the result of the judgment processing of the judgement section. 
     (9) An image processing program according to this disclosure makes a computer function as an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine; a judgement section for performing judgment processing as to whether predetermined two or more color areas are included in the image taken by the image acquisition section; and a notification section for performing notification processing depending on the result of the judgment processing of the judgement section. 
     (10) A label according to this disclosure is subjected to judgment processing by the above-mentioned image processing device as to whether predetermined two or more color areas are included, wherein the predetermined two or more color areas are disposed in a predetermined positional relationship. 
     This disclosure can be attained not only as an image processing device equipped with these characteristic processing sections but also as an image processing method wherein the processing to be performed by the characteristic processing sections included in the image processing device is performed stepwise. Furthermore, it is needless to say that the above-mentioned image processing program can be distributed on computer-readable non-transitory recording media, such as a CD-ROM (Compact Disc-Read Only Memory), or a communication network, such as the Internet. Moreover, this disclosure can also be attained such that part or whole of the image processing device is implemented as a semiconductor integrated circuit. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a view showing an installation example of an image processing system according to Embodiment 1; 
         FIG. 2  is a block diagram showing a functional configuration of the image processing system according to Embodiment 1; 
         FIG. 3  is a schematic view showing a forklift as viewed from above; 
         FIG. 4A  is a side view showing a helmet worn by a person; 
         FIG. 4B  is a top view showing the helmet worn by the person; 
         FIG. 5  is a view showing expressions in the Munsell color system for respective color labels; 
         FIG. 6A  is a view showing an example of a green area and a red area on an image; 
         FIG. 6B  is a view showing an example of a green area and a red area on an image; 
         FIG. 7  is a view showing an example of an image taken by a rearward monitoring camera; 
         FIG. 8  is a flow chart of the processing performed by an image processing device according to Embodiment 1; 
         FIG. 9  is a flow chart showing the details of threshold value setting processing (at S 4  of  FIG. 8 ); 
         FIG. 10  is a side view showing a helmet worn by a person; 
         FIG. 11  is a side view showing a helmet worn by a person; 
         FIG. 12  is a side view showing a helmet worn by a person; 
         FIG. 13  is a front view of a person; 
         FIG. 14  is a block diagram showing a functional configuration of an image processing system according to Embodiment 2; 
         FIG. 15  is a flow chart of the processing performed by an image processing device according to Embodiment 2; 
         FIG. 16  is a block diagram showing a functional configuration of an image processing system according to Embodiment 3; 
         FIG. 17  is a flow chart of the processing performed by an image processing device according to Embodiment 3; 
         FIG. 18  is a figure showing an example of a data table indicating the relationship between positions being held in a threshold value setting section and the threshold values of green areas; 
         FIG. 19  is a view showing an installation example of an image processing system according to Embodiment 4; 
         FIG. 20  is a block diagram showing a functional configuration of the image processing system according to Embodiment 4; 
         FIG. 21  is a schematic view showing the forklift as viewed from above; and 
         FIG. 22  is a flow chart of the processing performed by an image processing device according to Embodiment 4. 
     
    
    
     MODE FOR CARRYING OUT THE INVENTION 
     [Problem that the Invention is to Solve] 
     Since a forklift is structured such that a load is placed in an overhung state, the weight of the vehicle body is heavier than it looks. Hence, even if the forklift travels at low speed, the vehicle may make contact with a person, and there is a high possibility of causing a serious accident. This kind of problem will occur not only in industrial vehicles typified by a forklift but also in vehicle-type construction machines, such as a hydraulic shovel. 
     In Patent Document 1, since the candidate area of a person is identified using an HOG feature amount, in the case that the person squats or falls down, the candidate area of the person cannot be identified accurately. Furthermore, when a helmet is extracted, the image of the candidate area of the person is converted into an image as viewed just from the front. Hence, in the case that the person squats or falls down, the area of the helmet cannot be extracted accurately. As described above, the system described in Patent Document 1 has a problem of being weak against posture change. 
     In the safety device described in Patent Document 2, since it is assumed that the camera thereof is fixed to the ceiling, the device has a problem of being unable to detect a person in the case that the forklift travels at a position where the camera is not installed. 
     Accordingly, the present invention is intended to provide an image processing device, an image processing system and an image processing program being strong against the posture change of a person and capable of detecting a person being present around a vehicle at an arbitrary position where a vehicle categorized as an industrial vehicle or a vehicle-type construction machine travels. The present invention is also intended to provide a label that is detected accurately by image processing. 
     [Advantage of the Invention] 
     This disclosure can provide an image processing device, an image processing system and an image processing program being strong against the posture change of a person and capable of detecting a person being present around a vehicle at an arbitrary position where a vehicle categorized as an industrial vehicle or a vehicle-type construction machine travels. 
     Furthermore, this disclosure can also provide a label that is detected accurately by image processing. 
     [Summary of an Embodiment According to the Present Application] 
     First, a summary of an embodiment will be enumerated and described. 
     (1) An image processing device according to this embodiment is equipped with an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine; a judgement section for performing judgment processing as to whether predetermined two or more color areas having a predetermined positional relationship are included in the image taken by the image acquisition section; and a notification section for performing notification processing depending on the result of the judgment processing of the judgement section. 
     With this configuration, a judgment is made as to whether the predetermined two or more color areas having the predetermined positional relationship are included in the image taken by the imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine, and a notification depending on the result of the judgment processing can be given. Hence, by attaching a label having the predetermined two or more color areas to a person or the helmet worn by the person, the person can be detected. The processing for extracting these color areas can be performed in the case that the color areas are imaged by the imaging section. Hence, the image processing device is strong against the posture change of a person and can detect a person around the vehicle at an arbitrary position where the vehicle travels. 
     (2) Furthermore, the imaging section may include a rearward monitoring camera, which is installed at the position on the vehicle where the area behind the vehicle is allocated as the imaging area thereof; the image acquisition section may acquire the image of the area behind the vehicle taken by the rearward monitoring camera; and the judgement section may stop the judgment processing for the image of the area behind the vehicle in the case that the vehicle is traveling forward. 
     With this configuration, the area behind the vehicle and the areas around the sides of the vehicle are in the blind spots of the driver. Hence, a person being present in such a blind spot can be detected by performing judgment processing for the image of the area behind the vehicle taken by the rearward monitoring camera. Furthermore, in the case that a person is present in the blind spot, a notification can be given to the driver appropriately. Moreover, also in the case that the vehicle starts, there is a high possibility that the vehicle will make contact with a person. Hence, in the case that a person is present in the blind spot of the driver immediately before the forklift starts, a notification can be given to the driver appropriately by performing the judgment processing and notification processing in the case that the vehicle is stopping. Consequently, the vehicle can be prevented preliminarily from making contact with the person being present around the vehicle. In the case that the vehicle is traveling forward, the driver drives carefully, whereby it is not particularly necessary to monitor the area behind the vehicle. With this configuration, the judgment processing is stopped in the case that the vehicle travels forward. As a result, the fact that a person has been detected can be prevented from being unnecessarily notified to the driver. 
     (3) Moreover, the imaging section may further include a forward monitoring camera, which is installed at the position on the vehicle where the area ahead of the vehicle is allocated as the imaging area thereof; the image acquisition section may further acquire the image of the area ahead of the vehicle taken by the forward monitoring camera; and the judgement section may further perform the judgment processing for the image of the area ahead of the vehicle in the case that the vehicle is traveling forward. 
     With this configuration, in the case that the vehicle travels forward, the judgment processing is performed for the image of the area ahead of the vehicle taken by the forward monitoring camera. Hence, a person being present ahead of the vehicle can be detected. Furthermore, in the case that a person is present ahead of the vehicle, a notification can be given to the driver appropriately. Consequently, the vehicle can be prevented preliminarily from making contact with the person being present around the vehicle. 
     (4) What&#39;s more, the judgement section may include a color extraction section for extracting the predetermined two or more color areas on the basis of pixel values on a predetermined color space and of the respective pixels constituting the image and predetermined threshold values; the image acquisition section may acquire an image, taken by the imaging section, of a reference label having the predetermined two or more colors and placed at a predetermined position of the vehicle; and the image processing device may be further equipped with a threshold value setting section for setting the predetermined threshold values on the basis of the pixel values on the color space and of the image of the reference label. 
     With this configuration, the threshold values can be set on the basis of the pixel values of the reference label disposed in an environment similar to those of labels placed on a person and a helmet to be detected. Hence, the threshold values can be set accurately, whereby the areas can be extracted accurately. 
     (5) Still further, the threshold value setting section may set the predetermined threshold values in the case that a change in illuminance around the vehicle is detected. 
     By setting the threshold values in the case that the change in illuminance is detected as described above, the areas can be extracted accurately even in the case that the environment around the vehicle has changed. 
     (6) Furthermore, the judgement section may include a color extraction section for extracting the predetermined two or more color sections on the basis of the values on a predetermined color space and of the respective pixels constituting the image and predetermined threshold values, and the image processing device may be further equipped with a threshold value setting section for setting the predetermined threshold values on the basis of the position of the vehicle. 
     With this configuration, the threshold values can be set on the basis of the position of the vehicle. For example, by preliminarily associating the position of the vehicle with the threshold values, the threshold values in the case that the vehicle is traveling indoors can be changed so as to be different from the threshold values in the case that the vehicle is traveling outdoors. Hence, the areas can be extracted accurately even in the case that the environment around the vehicle has changed. 
     (7) Moreover, of the images acquired by the image acquisition section, the image of a mirror area that is taken by imaging the mirror installed on the vehicle may be subjected to the judgment processing by the judgement section. 
     With this configuration, even in the case that a person is shown over the mirror that is installed on the vehicle to confirm the blind spot, the judgment processing is performed for the image of the person. Hence, the person being present in the blind spot area can be detected accurately. 
     (8) An image processing system according to the embodiment is equipped with a label, which is placed on an object to be detected and on which predetermined two or more color areas are disposed in a predetermined positional relationship, and an image processing device for detecting the object to be detected, wherein the image processing device has an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine; a judgement section for performing judgment processing as to whether the predetermined two or more color areas are included in the image taken by the image acquisition section; and a notification section for giving a notification depending on the result of the judgment processing of the judgement section. 
     With this configuration, the label having the predetermined two or more color areas is placed on an object to be detected, such as a person. Furthermore, the image processing device can judge whether the predetermined two or more color areas are included in the image taken by the imaging section mounted on the vehicle categorized as an industrial vehicle or a vehicle-type construction machine and can give a notification depending on the result of the judgment processing. The processing for extracting these color areas can be performed in the case that the color areas are imaged by the imaging section. Hence, the image processing device is strong against the posture change of a person and can detect a person being present around the vehicle at an arbitrary position where the vehicle travels. 
     (9) An image processing program according to the embodiment makes a computer function as an image acquisition section for acquiring an image taken by an imaging section mounted on a vehicle categorized as an industrial vehicle or a vehicle-type construction machine, a judgement section for performing judgment processing as to whether predetermined two or more color areas are included in the image taken by the image acquisition section, and a notification section for performing notification processing depending on the result of the judgment processing of the judgement section. 
     With this program, the computer can be made to function as the above-mentioned image processing device. Hence, operations and effects similar to those of the above-mentioned image processing device can be attained. 
     (10) A label according to the embodiment is subjected to judgment processing by the above-mentioned image processing device as to whether predetermined two or more color areas are included, wherein the predetermined two or more color areas are disposed in a predetermined positional relationship. 
     With this configuration, the predetermined two or more color areas are disposed in the predetermined positional relationship on the label. Hence, by placing the label on an object to be detected, such as a person, the object to be detected can be detected accurately by the above-mentioned image processing device. 
     (11) Moreover, a predetermined clearance may be provided between the respective color areas. 
     With this configuration, even in the case that disturbances occur in an image taken by the imaging section due to vibrations and the like during the traveling of the vehicle, the color of an area can be prevented from being mixed with the color of the area adjacent thereto. Consequently, an object to be detected can be detected accurately by the above-mentioned image processing device. 
     (12) What&#39;s more, the respective color areas may be composed of fluorescent tapes, fluorescent paint or light emitting elements. 
     Hence, the label can be made easily recognizable even under environments in which illuminance is low, for example, at night or in cloudy weather. 
     [Details of Embodiments According to the Present Invention] 
     Embodiments according to this disclosure will be described below in detail using drawings. The embodiments to be described below are all desirable examples of this disclosure. The numerical values, the shapes, the materials, the components, the arrangement positions and connection modes of the components, the steps, the sequence of the steps, etc. to be described in the following embodiments are taken as examples and are not intended to limit this disclosure. This disclosure is specified by the claims. Hence, of the components according to the following embodiments, the components not described in the independent claims representing the highest concepts of the present invention are not necessarily required to attain the tasks of this disclosure, but they are described as components constituting further preferable modes. 
     Embodiment 1 
     An image processing system according to Embodiment 1 will be described below. 
     &lt;Configuration of the Image Processing System&gt; 
       FIG. 1  is a view showing an installation example of the image processing system according to Embodiment 1.  FIG. 2  is a block diagram showing a functional configuration of the image processing system according to Embodiment 1. 
     An image processing system  1  is a system for monitoring the periphery of a forklift  25  and is equipped with a rearward monitoring camera  20 , an image processing device  10 , a sound output device  30 , a display device  40 , a terminal device  50 , and a shift sensor  112 . The configuration of the image processing system  1  shown in  FIGS. 1 and 2 , however, is just an example, and the image processing system  1  may not be equipped with either one of the sound output device  30 , the display device  40  and the terminal device  50 . 
     In addition, a vehicle in which the image processing device  10 , the rearward monitoring camera  20 , the sound output device  30 , the display device  40  and the shift sensor  112  are installed is not limited to the forklift  25 ; these devices may be installed in industrial vehicles other than the forklift  25  or may also be installed in vehicle-type construction machines, such as a hydraulic shovel. In the case that the rearward monitoring camera  20  is installed in these vehicles, the camera can monitor the peripheries of these vehicles. 
     The rearward monitoring camera  20  constituting an imaging section is installed, for example, at a position where the area behind the forklift  25  can be imaged (for example, at the rear end position of the fork head guard of the forklift  25 ) and is used to take an image of the area behind the forklift  25 . The camera lens of the rearward monitoring camera  20  is, for example, a super-wide angle lens having a field angle of 120° or more. 
       FIG. 3  is a schematic view showing the forklift  25  as viewed from above. In  FIG. 3 , the left side is the area ahead of the forklift  25 , and the right side is the area behind the forklift  25 . As shown in  FIG. 3 , a rearward image taking area  21  to be monitored by the rearward monitoring camera  20  is set behind the forklift  25 . This rearward image taking area  21  is set, for example, so as to include the movable range of the forklift  25  in two seconds in the case that the forklift  25  travels at the maximum speed of 10 km/h. In other words, the rearward monitoring camera  20  is set at the position where the image of the rearward image taking area  21  can be taken. Hence, the rearward monitoring camera  20  can take the image of a person  71  being present inside the rearward image taking area  21 . The reason for this setting of the rearward image taking area  21  is that it is assumed that the driver can stop the forklift  25  within two seconds after the driver found the person  71 . Although a monocular camera is assumed to be used as the rearward monitoring camera  20 , a multiple camera, such as a stereo camera, may also be used. 
     A blind spot area  22  deviated from the rearward image taking area  21  of the forklift  25  may be generated sometimes behind the forklift  25 . A mirror  60  is installed inside the rearward image taking area  21  of the forklift  25  in order to cover this blind spot area  22 . In other words, the rearward monitoring camera  20  can take the image of a person  72  being present in the blind spot area  22  by disposing the mirror  60  so that a rearward image taking area  61  covers the blind spot area  22  in the case that the rearward monitoring camera  20  takes an image over the mirror  60 . Instead of the mirror  60 , another camera different from the rearward monitoring camera  20  may also be disposed to take the image of the blind spot area  22 . 
     The image processing device  10  is a computer installed in the forklift  25 . The image processing device  10  is connected to the rearward monitoring camera  20  and detects the persons  71  and  72  from the images of the rearward image taking areas  21  and  61  taken by the rearward monitoring camera  20 . In this embodiment, it is assumed that labels are attached to the persons  71  and  72 , each label being surely provided with predetermined two or more color areas that are disposed in a predetermined positional relationship. 
       FIG. 4A  is a side view showing a helmet worn by a person, and  FIG. 4B  is a top view showing the helmet. As shown in  FIGS. 4A and 4B , labels  90 A are attached to a helmet  80 . The label  90 A is composed of a blue label  90 B, a red label  90 R and a green label  90 G being arranged in parallel. As shown in  FIG. 4A , in the case that the width of the helmet  80  is 283 mm and the height thereof is 148 mm, the width of the label  90 A can be set to approximately 60 mm and the length thereof can be set to approximately 180 mm or more and 250 mm or less. A clearance area  90 S is provided between the blue label  90 B and the red label  90 R and is also provided between the red label  90 R and the green label  90 G. The clearance area  90 S is, for example, a black area and has a width of 2 to 3 mm. As shown in  FIG. 4B , a similar label  90 A is also attached to the upper side of the helmet  80 . Furthermore, the labels  90 A are also attached to the opposite side face and the front and rear sides of the helmet  80 . Since the labels  90 A are attached to all the positions as described above, the image of any one of the labels  90 A can be taken by the rearward monitoring camera  20  even if the person takes any posture (standing upright, squatting, etc.). 
     The label  90 A is composed the red label  90 R, the green label  90 G and the blue label  90 B having three primary colors of light.  FIG. 5  is a view showing expressions in the Munsell color system (JISZ 8721) for the respective color labels. In the figure, H, V and C represent hue, value and chroma, respectively. In other words, the color of the red label  90 R has the hue (H) in a range of 10P to 7.5YR, the value (V) in a range of 3 or more, and the chroma (C) in a range of 2 or more in the Munsell color system. The color of the green area  90 G has the hue (H) in a range of 2.5GY to 2.5BG, the value (V) in a range of 3 or more, and the chroma (C) in a range of 2 or more in the Munsell color system. The color of the blue label  90 B has the hue (H) in a range of 5BG to 5P, the value (V) in a range of 1 or more, and the chroma (C) in a range of 1 or more in the Munsell color system. However, the label  90 A is not limited to be composed of labels having three primary colors of light but may be composed of labels having other colors. 
     Furthermore, it is preferable that the blue label  90 B, the red label  90 R and the green label  90 G should be composed of fluorescent tapes or these labels should be coated with fluorescent paint. In this case, the labels can be made easily recognizable even under environments in which illuminance is low, for example, at night or in cloudy weather. Moreover, the labels can be recognized without using a special camera, such as an infrared camera. 
     The image processing device  10  detects the label  90 A from the image taken by the rearward monitoring camera  20 , thereby detecting a person. The detailed configuration of the image processing device  10  will be described later. 
     The sound output device  30  is installed, for example, in the vicinity of the driver&#39;s seat of the forklift  25  and is configured so as to include a speaker. The sound output device  30  is connected to the image processing device  10  and outputs a notification sound in order to notify the driver that the image processing device  10  has detected the person  71  or the person  72 . 
     The display device  40  is installed at a position where the driver of the forklift  25  can visually recognize the display device and is configured so as to include, for example, a liquid crystal display. The display device  40  is connected to the image processing device  10  and displays an image in order to notify that the image processing device  10  has detected the person  71  or the person  72 . 
     The terminal device  50  is a computer that is installed at a place away from the forklift  25 , such as a control room for controlling the forklift  25 . The terminal device  50  is connected to the image processing device  10  and outputs a sound or an image in order to notify that the image processing device  10  has detected the person  71  or the person  72 , or records the fact that the image processing device  10  has detected the person  71  or the person  72  together with time information as log information. The terminal device  50  and the image processing device  10  may be mutually connected by a mobile telephone line according to a communication standard, such as 4G, or a wireless LAN (Local Area Network), such as Wi-Fi (registered trademark). 
     The terminal device  50  may be, for example, a smart phone carried by the person  71  or the person  72 . In this case, the person  71  or the person  72  can be notified that he has been detected by the image processing device  10 , that is, the forklift  25  is present nearby. 
     Furthermore, the functions of the image processing device  10 , the rearward monitoring camera  20 , the sound output device  30  and the display device  40  may be provided for, for example, a smart phone or a camera-equipped computer. For example, by installing a smart phone at the position where the rearward monitoring camera  20  shown in  FIG. 1  is installed, the smart phone processes the image taken by the smart phone and detects the person  71  or the person  72 . Furthermore, the smart phone notifies the result of the detection by a sound or an image. However, in the case that the smart phone is installed at the position where the rearward monitoring camera  20  is installed, the driver cannot see the image. Hence, it may be possible that another tablet device or the like is installed at a position that can be visually recognized by the driver and that the tablet device displays the image transmitted from the smart phone. The tablet device and the smart phone may be mutually connected wirelessly according to a wireless communication standard, such as Wi-Fi (registered trademark), Bluetooth (registered trademark) or Zigbee (registered trademark). 
     Referring to  FIGS. 1 and 2 , the shift sensor  112  is installed in the vicinity of the shift lever and serves as a sensor for detecting the position of the shift lever. The shift sensor  112  is configured so as to include, for example, a displacement sensor or a switch. 
     &lt;Configuration of the Image Processing Device  10 &gt; 
     Referring to  FIG. 2 , the functional configuration of the image processing device  10  will be described in more detail. 
     The image processing device  10  is composed of a general-purpose computer that is equipped with a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), a communication I/F (interface), a timer, etc. The image processing device  10  is equipped with an image acquisition section  11 , a judgment section  12 , a color extraction section  13 , a notification section  14 , a threshold value setting section  15 , and a vehicle state judgment section  16  as functional components implemented by executing a computer program having been read from the HDD or the ROM to the RAM. 
     The image acquisition section  11  acquires images taken by the rearward monitoring camera  20  via the communication I/F. In other words, the images of the rearward image taking areas  21  and  61  shown in  FIG. 1  taken by the rearward monitoring camera  20  are acquired. 
     The judgement section  12  judges whether the predetermined two or more color areas (herein, the green area, the red area and the blue area) are included in the images acquired by the image acquisition section  11 . 
     More specifically, the judgement section  12  includes the color extraction section  13 . The color extraction section  13  extracts the green area, the red area and the blue area on the basis of pixel values on a color space and of the respective pixels constituting the image acquired by the image acquisition section  11  and predetermined threshold values. Herein, an HSV color space is assumed as the color space. Furthermore, the hue (H), the saturation (S) and the value (V) are assumed as the pixel values on the HSV color space. 
     In the case that the image acquired by the image acquisition section  11  is composed of pixel values of an RGB color space, the color extraction section  13  converts the pixel values of the RGB color space into the pixel values of the HSV color space and performs area extraction processing. The conversion from the pixel values of the RGB space into the pixel values of the HSV color space is performed, for example, by formulas 1 to 3 described below. 
     
       
         
           
             
               
                 
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     R, G and B herein respectively represent the red component, the green component and the blue component of the pixel before the conversion. Furthermore, MAX and MIN respectively represent the maximum value and the minimum value of the red components, the green components and the blue components of the pixels before the conversion. 
     It is assumed that, to the color extraction section  13 , for example, a range of 120±25 has been set as the range of the hue (H) of green, a range of 70 or more to 100 or less has been set as the range of the saturation (S) of green, and a range of 70 or more to 100 or less has been set as the range of the value (V) of green. In the case of a pixel having the hue (H) in the range of 120−25 or more to 120+25 or less, having the saturation (S) in the range of 70 or more to 100 or less and having the value (V) in the range of 70 or more to 100 or less, the color extraction section  13  extracts the pixel as a green pixel. Similarly, the color extraction section  13  extracts a red pixel from the image using the threshold values of the hue (H), the saturation (S) and the value (V) of red, and extracts a blue pixel from the image using the threshold values of the hue (H), the saturation (S) and the value (V) of blue. 
     The color extraction section  13  extracts the green area, the red area and the blue area by performing labeling processing for the green pixels, the red pixels and the blue pixels, respectively. The color extraction section  13  may eliminate noise areas by performing morphological dilation and erosion processing and performing filtering processing depending on the size of the area for the respective extracted green area, red area and blue area. 
     In the case that the red area, the green area and the blue area extracted by the color extraction section  13  have a predetermined positional relationship, the judgement section  12  judges that the green area, the red area and the blue area are included in the image acquired by the image acquisition section  11 . For example, in the case that the red area is present within a predetermined distance range from the position of the center of gravity of the green area on the image and that the blue area is present within a predetermined distance range from the position of the center of gravity of the red area on the image, the judgement section  12  judges that the green area, the red area and the blue area are included in the image. In the case that the judgement section  12  has judged that the green area, the red area and the blue area are included in the image, the judgement section  12  judges that a person is shown in the image and the person is present around the forklift  25 . 
       FIGS. 6A and 6B  are views each showing an example including the green area and the red area on the image. As shown in  FIG. 6A , in the case that a red area  82 R is included inside the predetermined distance range  84  indicated by a circle with the position of the center of gravity  83  of a green area  82 G as a center, it is judged that the red area  82 R is present within the predetermined distance range  84  from the position of the center of gravity  83  of the green area  82 G on the image. 
     On the other hand, as shown in  FIG. 6B , in the case that the red area  82 R is not included inside the predetermined distance range  84  indicated by the circle with the position of the center of gravity  83  of the green area  82 G as a center, it is judged that the red area  82 R is not present within the predetermined distance range  84  from the position of the center of gravity  83  of the green area  82 G on the image. 
     The diameter of the circle of the predetermined distance range  84  may herein be made equal to, for example, the longest side of the green area  82 G. In the case that the green area  82 G is an area having a shape other than a rectangular shape, the length of the longest side of the circumscribed rectangle of the green area  82 G may be used as the diameter of the circle of the predetermined distance range  84 . However, the diameter may have values other than these values. 
     The notification section  14  performs notification processing depending on the result of the judgment processing of the judgement section  12 . For example, in the case that the judgement section  12  has judged that a person is present around the forklift  25 , the notification section  14  transmits a predetermined sound signal to the sound output device  30  via the communication I/F, thereby outputting a notification sound to the sound output device  30 . Hence, a notification indicating that the person is present around the forklift  25  is given to the driver. 
     Furthermore, in the case that the judgement section  12  has made a similar judgement, the notification section  14  transmits a predetermined image signal to the display device  40  via the communication I/F, thereby making the display device  40  display an image indicating that the person has been detected. Hence, a notification indicating that the person is present around the forklift  25  is given to the driver. 
     Moreover, in the case that the judgement section  12  has made a similar judgement, the notification section  14  transmits information indicating that the person has been detected to the terminal device  50  via the communication I/F, thereby making the terminal device  50  perform the output processing of a sound or an image or perform the recording processing of log information. At the time, the notification section  14  may transmit information indicating the detection time. 
     On the basis of the pixel values on the color space and of the image of a reference label described later and attached to the forklift  25 , the threshold value setting section  15  sets threshold values that are used when the color extraction section  13  extracts the respective color areas. 
     The reference label attached to the forklift  25  is herein described.  FIG. 7  is a view showing an example of an image taken by the rearward monitoring camera  20 . A reference label  100  is attached to a predetermined position on the vehicle body of the forklift  25 . The reference label  100  is desirably a label made of the same material as that of the label  90 A. The reference label  100  includes a blue label  100 B, a red label  100 R and a green label  100 G. The colors of the red label  1008 , the green label  100 G and the blue label  100 B are the same as the colors of the red label  90 R, the green label  90 G and the blue label  90 B, respectively. 
     However, the attaching position of the reference label  100  is not limited to the vehicle body of the forklift  25 ; for example, as shown in  FIG. 7 , a reference label  100 A may be attached to a position in an environment similar to the environment in which a person is present, such as a rod-like member for supporting the mirror  60 . The reference label  100 A includes the blue label  100 B, the red label  100 R, and the green label  100 G as in the case of the reference label  100 . In the case that the reference label  100 A is provided on a face almost vertical to the ground as described above, the reference label  100 A is less affected by sun light and illumination light than the reference label  100  attached to the vehicle body. Hence, in the case that the threshold values are set using the image obtained by imaging the reference label  100 A, the threshold values can be set more accurately than in the case that the threshold values are set using the image obtained by imaging the reference label  100 . 
     The threshold value setting section  15  sets the threshold values so that the blue label  100 B, the red label  100 R and the green label  100 G in the image are surely detected. In other words, the threshold value setting section  15  sets the threshold values so that the pixel values on the HSV color space and of the respective color labels are included within the threshold values of the colors. The details of the method for setting the threshold values will be described later. 
     The vehicle state judgment section  16  acquires the detection result of the position of the shift lever from the shift sensor  112  via the communication I/F and judges whether the shift range is the R range (reverse range) on the basis of the acquired detection result of the position. In the case that the shift range is the R range and the forklift  25  is traveling, it is assumed that the forklift  25  is traveling rearward linearly or traveling rearward while turning or performing both the operations. However, in the case that the shift range is the R range and the brake is applied, the above-mentioned operation is not performed; however, when the brake is released, the above-mentioned operation is started, whereby the state of the above-mentioned case is assumed to be the preparation state of the above-mentioned operation. 
     The judgement result of the state of the vehicle by the vehicle state judgment section  16  is used to control the operation of the image processing device  10 . 
     &lt;The Flow of the Processing of the Image Processing Device  10 &gt; 
     Next, the flow of the processing performed by the image processing device  10  will be described. 
       FIG. 8  is a flow chart of the processing performed by the image processing device  10  according to Embodiment 1. 
     On the basis of the detection result of the position of the shift lever by the shift sensor  112 , the vehicle state judgement section  16  judges whether the shift range is the R range (at S 1 ). 
     In the case that the vehicle state judgement section  16  has judged that the shift range is not the R range (NO at S 1 ), the processing advances to step S 9 . For example, in the case that the shift range is the D range (drive range) and that the forklift  25  is traveling forward, the processing advances to step S 9 . 
     In the case that the vehicle state judgement section  16  has judged that the shift range is the R range (YES at S 1 ), the image acquisition section  11  acquires the image taken by the rearward monitoring camera  20  (at S 2 ). 
     The threshold value setting section  15  judges whether the present time is threshold value updating timing (at S 3 ). In Embodiment 1, it is assumed that the threshold values are changed periodically at predetermined time intervals. For example, the threshold values may be changed at intervals of one minute. In other words, in the case that a predetermined time has passed after the threshold values were set at the last time or after the image processing device  10  started operation, the threshold value setting section  15  judges that the present time is the threshold updating timing; in the case that the predetermined time has not passed, the threshold value setting section  15  judges that the present time is not the threshold updating timing. 
     In the case that the present time is the threshold updating timing (YES at S 3 ), the threshold value setting section  15  sets the threshold values (at S 4 ). Threshold value setting processing (at S 4 ) will be described later. 
     The judgement section  12  extracts the image of a mirror area from the image acquired by the image acquisition section  11  and expands the image at a predetermined expansion (for example, two times) (at S 5 ). For example, the mirror  60  is shown in the image as shown in  FIG. 7 , and the judgement section  12  expands the image of the area of the mirror  60  at the predetermined expansion. In order that the mirror  60  having a small area reflects the wide-range blind spot area  22  having a wide range, a convex mirror is usually used as the mirror  60 . There is a problem that the mirror image of a convex mirror is smaller than the image that is obtained by directly imaging the same object. Hence, the image of the area of the mirror  60  is expanded, whereby the judgement processing (area extraction processing) can be performed with the same accuracy as in the case that the same object is directly imaged. However, the processing (at S 5 ) for expanding the image of the area of the mirror  60  is not essential. 
     The color extraction section  13  extracts the red area, the green area and the blue area from the image (at S 6 ). At the time, the color extraction section  13  performs the area extraction processing for each of the image from which the mirror area is eliminated and the image in which the mirror area is expanded. Hence, the area of the person shown in the mirror  60  can be prevented from being doubly detected. 
     The judgement section  12  judges whether the red area, the green area and the blue area extracted by the color extraction section  13  have a predetermined positional relationship (at S 7 ). For example, it is assumed that the red label  90 R, the green label  90 G and the blue label  90 B shown in  FIG. 4A  have been extracted as the red area, the green area and the blue area, respectively. The judgement section  12  calculates the positions of the center of gravity of the red label  90 R, the green label  90 G and the blue label  90 B. In the case that the distance between the position of the center of gravity of the green label  90 G and the position of the center of gravity of the red label  90 R is within a predetermined distance or less and that the distance between the position of the center of gravity of the red label  90 R and the position of the center of gravity of the blue label  90 B is within a predetermined distance or less, the judgement section  12  judges that the red label  90 R, the green label  90 G and the blue label  90 B have a predetermined positional relationship. 
     In the case that the three color areas have the predetermined positional relationship (YES at S 7 ), the judgement section  12  judges that a person is shown in the image, and the notification section  14  notifies that the person has been detected around the forklift  25  to the sound output device  30 , the display device  40  and the terminal device  50  (at S 8 ). The notification processing by the notification section  14  may be performed, for example, in the case that the distance between the rearward monitoring camera  20  and the person is within a predetermined distance (for example, 3 m). The distance between the rearward monitoring camera  20  and the person is herein determined on the basis of the size of the label  90 A on the image extracted by the color extraction section  13 . In other words, the notification section  14  may have a table indicating the relationship between the size of the label  90 A and the distance and may determine the distance by referring to this table. Furthermore, in order to improve the accuracy of the detection, the notification section  14  may perform the notification processing only in the case that a person away from the rearward monitoring camera  20  within the predetermined distance is detected continuously a predetermined number of times (for example, five times) or more. 
     In the case that the three color areas do not have the predetermined positional relationship (NO at S 7 ), the processing advances to step S 9 . 
     After the notification processing (at S 8 ) is ended, in the case that the present time has become the end timing of the processing (YES at S 9 ), the image processing device  10  ends the processing. The end timing of the processing is, for example, the timing at which the image processing device  10  receives the signal indicating that the engine of the forklift  25  is stopped. 
     In the case that the present time is not the end timing of the processing (NO at S 9 ), the processing returns to step S 1 , and the processing of steps S 1  to S 8  is performed repeatedly. 
       FIG. 9  is a flow chart showing the details of the threshold value setting processing (at S 4  of  FIG. 8 ). 
     The threshold value setting section  15  performs the processing of steps S 41  to S 44  (loop A), described later, for the respective colors of red, green and blue to be subjected to the threshold value setting processing. 
     Although red is taken as a target color in the following description, similar processing is also performed in the case that the target colors are green and blue. 
     The threshold value setting section  15  calculates the averages of the hue (H), the saturation (S) and the value (V) in the area of the red label  100 R from the image acquired by the image acquisition section  11  (at S 41 ). In other words, the threshold value setting section  15  converts the red component (R), the green component (G) and the blue component (B) on the RBG color space and of the respective pixels in the area of the red label  100 R into the hue (H), the saturation (S) and the value (V) in the HSV color space, and calculates the averages of the hue (H), the saturation (S) and the value (V) in the area of the red label  100 R. The conversion from the pixel values in the RGB space into the pixel values in the HSV color space is performed according to the formulas 1 to 3 described above. 
     The threshold value setting section  15  sets the range of the average of the hue (H)±25 as the range of the hue (H) of the red area (at S 42 ). 
     The threshold value setting section  15  sets the range of (the average of the saturation (S)−20) or more to 100 or less as the range of the saturation (S) of the red area (at S 43 ). 
     The threshold value setting section  15  sets the range of (the average of the value (V)−20) or more to 100 or less as the range of the value (V) of the red area (at S 44 ). 
     Hence, the threshold value setting section  15  can set the threshold values of the hue (H), the saturation (S) and the value (V) on the basis of which the area of the red label  100 R can be extracted. 
     &lt;Effects of Embodiment 1&gt; 
     As described above, with Embodiment 1, the three color labels are disposed on the helmet  80  in the predetermined positional relationship. Furthermore, the judgement section  12  extracts the three color areas from the image taken by the rearward monitoring camera  20  and judges whether the three color areas are disposed in the predetermined positional relationship. Hence, the judgement section  12  judges whether a person is present around the forklift  25 . The processing for extracting the color areas can be performed in the case that the color areas are projected on the rearward monitoring camera  20 . Thus, even in the case that the person has changed his posture, he can be detected stably. Furthermore, unlike the technology described in Patent Document 2, the detection range of the person is not limited. Consequently, the person being present around the forklift  25  can be detected at an arbitrary position where the forklift  25  travels. 
     Moreover, in the case that the shift range is the R range, that is, in the case that the forklift  25  is traveling rearward linearly or traveling rearward while turning or performing both the operations, the image processing device  10  performs processing (image acquisition processing, judgement processing, notification processing, etc.) for detecting a person. Hence, in the case that a person is present behind the forklift  25 , that is, in the blind spot of the driver, the image processing device  10  can appropriately give a notification to the driver. 
     What&#39;s more, even if the brake has been applied, in the case that the shift range is the R range, the image processing device  10  performs processing for detecting a person. Hence, in the case that a person is present in the blind spot of the driver immediately before the forklift  25  starts, a notification can be given to the driver appropriately. 
     Furthermore, in the case that the forklift  25  is traveling forward, the image processing device  10  is configured so as not to perform processing for detecting a person. In the case that the forklift  25  is traveling forward, it is not necessary to monitor the area behind the forklift  25 . In other words, even if a person is present behind the forklift  25 , the presence of the person is not required to be notified to the driver. Consequently, with this configuration, the fact that a person has been detected can be prevented from being unnecessarily notified to the driver. 
     Furthermore, the threshold value setting section  15  sets the threshold values on the basis of the pixel values of the reference label  100  that has been disposed in an environment similar to that of the label  90 A placed on the helmet worn by a person. Consequently, the threshold values can be set accurately, whereby the color extraction section  13  can accurately extract the label  90 A. 
     Moreover, after the judgement section  12  has expanded the image of the area of the mirror  60  in the image at a predetermined expansion, the area extraction processing for the respective colors by the color extraction section  13  and the judgment processing by the judgement section  12  are performed. In other words, even in the case that a person is shown over the mirror  60  that is installed on the forklift  25  to confirm the blind spot, the processing is performed after the image of the person has been expanded. Hence, the person being present in the blind spot area can be detected accurately. Although the judgment processing (area extraction processing) is performed after the mirror image of the mirror  60  has been expanded in Embodiment 1, the expansion of the image is not essential. In other words, the judgment processing (area extraction processing) may be performed without expanding the image of the area of the mirror  60 . 
     What&#39;s more, the predetermined two or more color areas (the red label  90 R, the green label  90 G and the blue label  90 B) are disposed on the label  90 A in the predetermined positional relationship. Hence, in the case that the label  90 A is placed on a person, the person can be detected by the image processing device  10 . 
     Still further, in the label  90 A, the clearance area  90 S is provided between the color labels adjacent to each other. Hence, even in the case that disturbances occur in the image taken by the rearward monitoring camera  20  due to vibrations and the like during the traveling of the forklift  25 , the color of a color label can be prevented from being mixed with the color of the color label adjacent thereto when the image is taken. Consequently, a person can be detected accurately by the image processing device  10 . 
     (Modification) 
     The labels to be attached to the helmet are not limited to those shown in  FIGS. 4A and 4B . For example, the label may be composed of a two-color label.  FIG. 10  is a side view showing a helmet worn by a person. As shown in  FIG. 10 , a label  90 C composed of the red label  90 R and the green label  90 G is attached to the helmet  80 . As shown in  FIG. 10 , in the case that the width of the helmet  80  is 283 mm and the height thereof is 148 mm, the width of the label  90 C can be set to approximately 40 mm and the length thereof can be set to approximately 180 mm or more and 250 mm or less. The clearance area  90 S is provided between the red label  90 R and the green label  90 G. Labels similar to the label  90 C are also attached to the opposite side face, the front and rear sides, and the upper side of the helmet  80 . 
     Furthermore, the shapes of the respective color labels to be attached to the helmet may be different for each color, and the arrangement of the labels may be made more complicated.  FIG. 11  is a side view showing a helmet worn by a person. As shown in  FIG. 11 , a label  90 D may be attached to the helmet  80 . The label  90 D includes the red label  90 R disposed at the center, the green labels  90 G disposed at positions adjacent to the upper right and lower left of the red label  90 R, and the blue labels  90 B disposed at positions adjacent to the upper left and lower right of the red label  90 R. As clearly shown in  FIG. 11 , the size of the red label  90 R is larger than the sizes of the blue labels  90 B and the green labels  90 G. Furthermore, the clearance areas  90 S are provided between the respective labels. Moreover, labels similar to the label  90 D are also attached to the opposite side face, the front and rear sides, and the upper side of the helmet  80 . 
     Furthermore, each of the color labels to be attached to the helmet may be composed of a light emitting element, such as an LED (Light Emitting Diode) or an organic EL (electroluminescence).  FIG. 12  is a side view showing a helmet worn by a person. As shown in  FIG. 12 , a label  91  is placed on the helmet  80 . The label  91  includes a blue label  91 B composed of a blue LED, a red label  91 R composed of a red LED, and a green label  91 G composed of a green LED. Each LED is driven by a secondary battery, such as a lithium ion battery. Moreover, labels similar to the label  91  are also placed on the opposite side face, the front and rear sides, and the upper side of the helmet  80 . Since the label  91  is composed of LEDs, the label  91  can be made easily recognizable even under environments in which illuminance is low, for example, at night or in cloudy weather. 
     What&#39;s more, the labels may also be placed on clothes, armbands, etc. worn by a person, instead of the helmet  80 .  FIG. 13  is a front view of a person. This person wears armbands on which labels  90 F are placed around his both arms. The label  90 F is composed of the blue label  90 B, the red label  90 R and the green label  90 G, and the clearance area  90 S is provided between the respective labels. 
     Embodiment 2 
     In Embodiment 1, the threshold value setting section  15  changes the threshold values periodically at predetermined time intervals; however, in Embodiment 2, the threshold value setting section  15  changes the threshold values in the case that a change in illuminance around the forklift  25  has been detected. 
     In the following descriptions, portions common to Embodiment 1 are not described repeatedly, and portions different from Embodiment 1 will be mainly described. 
       FIG. 14  is a block diagram showing a functional configuration of an image processing system according to Embodiment 2. 
     An image processing system  1  A is further equipped with an ambient light sensor  115  in the configuration of the image processing system  1  according to Embodiment 1 shown in  FIG. 2 . The ambient light sensor  115  is a sensor for detecting the illuminance around the forklift  25 . The ambient light sensor  115  is configured so as to include, for example, a light receiving element. The ambient light sensor  115  is provided, for example, in the vicinity of the rearward monitoring camera  20 . However, the illuminance around the forklift  25  may be judged from the image taken by the rearward monitoring camera  20  without using the ambient light sensor  115 . 
       FIG. 15  is a flow chart of the processing performed by an image processing device  10  according to Embodiment 2. 
     The processing of steps S 1 , S 2  and S 4  to S 9  is similar to the processing of steps S 1 , S 2  and S 4  to S 9  shown in  FIG. 8 . In Embodiment 2, the processing of step S 13  is performed instead of the processing of step S 3  shown in  FIG. 8 . 
     In other words, the threshold value setting section  15  holds the illuminance detected by the ambient light sensor  115  and judges whether the illuminance around the forklift  25  has changed, on the basis of the illuminance difference between the current illuminance and the illuminance having been held at the time when the threshold value were set at the last time (at S 13 ). In other words, in the case that the illuminance difference is not less than a predetermined illuminance threshold value, the threshold value setting section  15  judges that the illuminance has changed (detects the change in illuminance); and in the case that the illuminance difference is less than the predetermined illuminance threshold value, the threshold value setting section  15  judges that the illuminance has not changed (does not detect the change in illuminance). 
     In the case that the change in illuminance has been detected, the threshold value setting section  15  performs the threshold value setting processing (at S 4 ). 
     At the first judgment processing (at S 13 ) immediately after the start of the image processing device  10 , the threshold value setting section  15  may be sure to detect the change in illuminance and then may perform the threshold value setting processing (at S 4 ). 
     As described above, with Embodiment 2, in the case that the change in illuminance has been detected, the threshold values can be set. Hence, even in the case that the environment around the forklift  25  has changed, the color areas can be extracted accurately. Consequently, a person being present around the forklift  25  can be detected accurately. 
     Embodiment 3 
     In Embodiment 1, the threshold value setting section  15  changes the threshold values periodically at predetermined time intervals; however, in Embodiment 3, the ambient light sensor  115  sets the threshold values on the basis of the position of the forklift  25 . 
     In the following descriptions, portions common to Embodiment 1 are not described repeatedly, and portions different from Embodiment 1 will be mainly described. 
       FIG. 16  is a block diagram showing a functional configuration of an image processing system according to Embodiment 3. 
     An image processing system  1  B is further equipped with a position sensor  114  in the configuration of the image processing system  1  according to Embodiment 1 shown in  FIG. 2 . The position sensor  114  is a sensor for detecting the position of the forklift  25 . The position sensor  114  is configured so as to include, for example, a GPS (Global Positioning System) sensor. Although the position sensor  114  can be installed at an arbitrary position on the forklift  25 , it is preferable that the position sensor should be installed at a position where the radio waves from the GPS satellites can be received easily. 
       FIG. 17  is a flow chart of the processing performed by an image processing device  10  according to Embodiment 3. 
     The processing of steps S 1 , S 2  and  5  to S 9  is similar to the processing of steps S 1 , S 2  and S 5  to S 9  shown in  FIG. 8 . In Embodiment 3, the processing of steps S 23  and S 24  is performed instead of the processing of steps S 3  and S 4  shown in  FIG. 8 . 
     In other words, the threshold value setting section  15  acquires position information from the position sensor  114  (at S 23 ). The position information is, for example, information indicating the latitude and longitude of the forklift  25 . 
     On the basis of the obtained position information, the threshold value setting section  15  determines the threshold values at the time when the respective color areas are extracted (at S 24 ).  FIG. 18  is a figure showing an example of a data table indicating the relationship between positions being held in the threshold value setting section  15  and the threshold values of the green areas. This data table indicates the threshold values of the hue (H), the saturation (S) and the value (V) for extracting the green area in the case that the forklift  25  is present within the position indicated by the data table. 
     For example, in the case that the position information (longitude, latitude) acquired from the position sensor  114  is within the range of (34° 40′39″, 135°26′8″) to (34°40′36″, 135°26′13″), the threshold value setting section  15  sets a range of 120±25 as the range of the hue (H) of the green area, sets a range of 70 or more to 100 or less as the range of the saturation (S) of the green area, and sets a range of 70 or more to 100 or less as the range of the value (V) of the green area. 
     Also for the red area and the blue area, the threshold value setting section  15  holds a data table indicating the relationship between the position and the threshold value in a similar way, and sets the threshold values of the red area and the blue area on the basis of the position information acquired from the position sensor  114 . 
     As described above, with Embodiment 3, the threshold values can be set on the basis of the position of the forklift  25 . Hence, for example, the threshold values in the case that the forklift  25  is traveling indoors can be changed so as to be different from the threshold values in the case that the forklift  25  is traveling outdoors. Hence, even in the case that the environment around the forklift  25  has changed, the color areas can be extracted accurately. Consequently, a person being present around the forklift  25  can be detected accurately. 
     Embodiment 4 
     In Embodiments 1 to 3, an example in which a person being present behind the forklift  25  is detected has been described. In Embodiment 4, an example in which not only a person being present behind the forklift  25  but also another person being present ahead of the forklift  25  are detected will be described. 
     In the following descriptions, portions common to Embodiments 1 to 3 are not described repeatedly, and portions different from Embodiments 1 to 3 will be mainly described. 
       FIG. 19  is a view showing an installation example of an image processing system according to Embodiment 4.  FIG. 20  is a block diagram showing a functional configuration of an image processing system according to Embodiment 4. 
     An image processing system  1 C is further equipped with a forward monitoring camera  26  in the configuration of the image processing system  1  according to Embodiment 1 shown in  FIG. 2 . 
     The forward monitoring camera  26  constituting an imaging section together with the rearward monitoring camera  20  is installed, for example, at a position where the area ahead of the forklift  25  can be imaged (for example, a rod-like jig provided on the forklift  25 ) and is used to take images ahead of the forklift  25 . The camera lens of the forward monitoring camera  26  is, for example, a super-wide angle lens having a field angle of 150° or more. 
       FIG. 21  is a schematic view showing the forklift  25  as viewed from above. In  FIG. 21 , the left side is the area ahead of the forklift  25 , and the right side is the area behind the forklift  25 . As shown in  FIG. 21 , the forward image taking area  27  to be monitored by the forward monitoring camera  26  and the rearward image taking area  21  to be monitored by the rearward monitoring camera  20  are set ahead of and behind the forklift  25 , respectively. The rearward image taking area  21  has been described in Embodiment 1. The forward image taking area  27  is set, for example, so as to include the movable range of the forklift  25  in two seconds in the case that the forklift  25  travels at the maximum speed of 10 km/h. In other words, the forward monitoring camera  26  is set at the position where the image of the forward image taking area  27  can be taken. Hence, the forward monitoring camera  26  can take the image of a person being present inside the forward image taking area  27 . The reason for this setting of the forward image taking area  27  is that it is assumed that the driver can stop the forklift  25  within two seconds after the driver found the person. Although a monocular camera is assumed to be used as the forward monitoring camera  26 , a multiple camera, such as a stereo camera may also be used. 
     The image acquisition section  11  provided in the image processing device  10  acquires images taken by the forward monitoring camera  26  or images taken by the rearward monitoring camera  20  via the communication I/F. 
     The vehicle state judgment section  16  performs the following processing in addition to the judgment processing described in Embodiment 1. In other words, the vehicle state judgment section  16  acquires the detection result of the position of the shift lever from the shift sensor  112  via the communication I/F and judges whether the shift range is the D range on the basis of the acquired detection result of the position. In the case that the shift range is the D range and the forklift  25  is traveling, it is assumed that the forklift  25  is traveling forward linearly or traveling forward while turning or performing both the operations. However, in the case that the shift range is the D range and the brake is applied, the above-mentioned operation is not performed; however, when the brake is released, the above-mentioned operation is started, whereby the state of the above-mentioned case is assumed to be the preparation state of the above-mentioned operation. 
     Next, the flow of the processing performed by the image processing device  10  will be described. 
       FIG. 22  is a flow chart of the processing performed by the image processing device  10  according to Embodiment 4. On the basis of the detection result of the position of the shift lever by the shift sensor  112 , the vehicle state judgement section  16  judges whether the shift range is the R range (at S 1   a ). 
     In the case that the vehicle state judgement section  16  has judged that the shift range is the R range (YES at S 1   a ), the image acquisition section  11  acquires the image taken by the rearward monitoring camera  20  (at S 2   a ). After that, the processing of S 3  to S 9  is performed for the image taken by the rearward monitoring camera  20 . The processing of S 3  to S 9  is the same as described in Embodiment 1. 
     In the case that the vehicle state judgement section  16  has judged that the shift range is not the R range (NO at S 1   a ), the vehicle state judgement section  16  judges whether the shift range is the D range on the basis of the detection result of the position of the shift lever (at S 1   b ). However, it may be assumed that the shift range for forward movement, such as the L range or the 2nd range, is included in the D range. In other words, in the case that the shift range is the shift range for forward movement, such as the L range, the vehicle state judgement section  16  may judge that the shift range is the D range. 
     In the case that the vehicle state judgement section  16  has judged that the shift range is the D range (YES at S 1   a ), the image acquisition section  11  acquires the image taken by the forward monitoring camera  26  (at S 2   b ). After that, the processing of steps S 3  to S 9  is performed for the image taken by the forward monitoring camera  26 . The processing of steps S 3  to S 9  is the same as described in Embodiment 1, except that the image to be processed is the image taken by the forward monitoring camera  26 . Hence, in the case that a pedestrian is present inside the forward image taking area  27  of the forward monitoring camera  26 , the pedestrian can be detected, and the result of the detection of the pedestrian can be notified to the driver. 
     In the case that the vehicle state judgment section  16  has judged that the shift range is neither the R range nor the D range (NO at S 1   b ), the processing advances to step S 9 . For example, in the case that the shift range is the P range and the forklift  25  is stopping, the processing advances to step S 9 . 
     As described above, with Embodiment 4, in the case that the forklift  25  is moving forward, processing (image acquisition processing, judgement processing, notification processing, etc.) for detecting a person is performed for the image of the area ahead of the forklift  25  taken by the forward monitoring camera  26 . Hence, a person being present ahead of the forklift  25  can be detected. Furthermore, in the case that a person is present ahead of the forklift, a notification can be given to the driver appropriately. Hence, the forklift  25  can be prevented preliminarily from making contact with the person being present around the forklift  25 . 
     &lt;Supplementary Note&gt; 
     Although the image processing systems  1  according to the embodiments of this disclosure have been described above, this disclosure is not limited to the embodiments. 
     For example, with the above-mentioned embodiments, it is assumed that the label is placed on a person and that the image processing device  10  detects the person; however, the label may be placed on an object other than a person. For example, the label may be attached to the vicinity of a place where the forklift  25  is prohibited to enter, whereby the image processing device  10  may detect that the forklift  25  has approached the place. Hence, the fact that the forklift  25  has approached the entry prohibited place can be notified, for example, to the driver. 
     Furthermore, although the color extraction section  13  of the above-mentioned image processing device  10  has extracted the color areas by subjecting the hue (H), the saturation (S) and the value (V) on the HSV color space to the threshold value processing, the objects to be subjected to the threshold value processing are not limited to the hue (H), the saturation (S) and the value (V) on the HSV color space. For example, the colors of the respective coordinates on an image may be represented by the hue (H), the value (V) and the chroma (C) in the Munsell color system, and color areas may be extracted by subjecting the hue (H), the value (V) and the chroma (C) to the threshold value processing. Moreover, the color areas may be extracted by subjecting the red components (R), the green components (G) and the blue components (B) of the respective coordinates on the image to the threshold value processing. 
     Furthermore, the above-mentioned label to be placed on a person or the like may be configured as described below. 
     In other words, the label is an object to be judged by the above-mentioned image processing device  10  whether the predetermined two or more color areas are included in the label, 
     the predetermined two or more color areas are disposed in the predetermined positional relationship, 
     the predetermined two or more color areas include a first color label, a second color label and a third color label, 
     the color of the first color label has the hue (H) in a range of 10P to 7.5YR, the value (V) in a range of 3 or more, and the chroma (C) in a range of 2 or more in the Munsell color system, the color of the second color label has the hue (H) in a range of 2.5GY to 2.5BG, the value (V) in a range of 3 or more, and the chroma (C) in a range of 2 or more in the Munsell color system, and 
     the color of the third color label has the hue (H) in a range of  5 BG to  5 P, the value (V) in a range of 1 or more, and the chroma (C) in a range of 1 or more in the Munsell color system. 
     Moreover, part or whole of the components constituting the above-mentioned image processing device  10  may be composed of a single system LSI. The system LSI is a super-multifunctional LSI manufactured by integrating a plurality of component sections on a single chip, more specifically, a computer system composed of a microprocessor, ROM and RAM. A computer program is stored in the RAM. The microprocessor operates according to the computer program, whereby the system LSI performs the functions thereof. 
     Furthermore, the computer program for making the computer function as the image processing device  10  may be recorded on computer-readable non-transitory recording media, such as a hard disk drive, a CD-ROM and a semiconductor memory. The computer program may be transmitted via an electric communication line, a wireless or wired communication line, a network typified by the Internet, data broadcasting, etc. 
     Moreover, the respective steps included in the above-mentioned computer program may be performed by a plurality of computers. What&#39;s more, the above-mentioned embodiments and the above-mentioned modification may be combined mutually. 
     The embodiments having been disclosed this time are to be considered exemplary and nonrestrictive in all respects. The range of this disclosure is intended to include, instead of the above-mentioned meanings, all the modifications within the meanings and ranges mentioned in the claims and being equivalent to the claims. 
     DESCRIPTION OF REFERENCE NUMERALS AND SIGNS 
       1 ,  1 A,  1 B,  1 C image processing system 
       10  image processing device 
       11  image acquisition section 
       12  judgement section 
       13  color extraction section 
       14  notification section 
       15  threshold value setting section 
       16  vehicle state judgment section 
       20  rearward monitoring camera 
       21  rearward image taking area 
       22  blind spot area 
       25  forklift 
       26  forward monitoring camera 
       27  forward image taking area 
       30  sound output device 
       40  display device 
       50  terminal device 
       60  mirror 
       61  rearward image taking area 
       71 ,  72  person 
       80  helmet 
       82 R red area 
       82 G green area 
       83  position of the center of gravity 
       84  predetermined distance range 
       90 A,  90 C,  90 D,  90 F,  91  label 
       90 B,  91 B,  100 B blue label 
       90 G,  91 G,  100 G green label 
       90 R,  91 R,  100 R red label 
       90 S clearance area 
       100 ,  100 A reference label 
       112  shift sensor 
       114  position sensor 
       115  ambient light sensor