Patent Publication Number: US-10769805-B2

Title: Method, image processing device, and system for generating depth map

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the priority benefit of Taiwan application serial no. 107116405, filed on May 15, 2018. The entirety of the above-mentioned patent application is hereby incorporated by reference herein and made a part of this specification. 
     BACKGROUND 
     Technical Field 
     The invention relates to a method, an image processing device, and a system for image processing. More particularly, the invention relates to a method, an image processing device, and a system for generating a depth map. 
     Description of Related Art 
     Through the development of frameworks in image processing, stereo vision has been extensively applied in many fields such as structured light, stereo image, distance detection, surveillance, and so forth. Stereo vision generally involves two stages. In the first stage, depth information is generated by using a depth camera, a stereo camera, or a related algorithm. In the second stage, a stereo image is generated by using the depth information. Hence, accurate depth information is rigidly important to provide a pleasant stereo viewing experience. 
     The fundamental of depth computation in stereo vision is to search for a same object from left and right images and determine an object distance on a basis of offsets of the object appearing in the two images (i.e. disparity). However, in a case where an object has less features such that no significant difference exists between neighboring pixels, this could result in error recognition and thereby obtain inaccurate depth information. 
     SUMMARY 
     The invention provides a method, an image processing device, and a system for generating a depth map, where a disparity map of a scene would be able to be precisely computed and the performance of subsequent stereo vision applications would be thereby enhanced. 
     In an embodiment of the invention, the method includes the following steps. A first original image and a second original image are obtained, and first edge blocks corresponding to the first original image and second edge blocks corresponding to the second original image are obtained. Depth information of edge blocks is generated according to the first edge blocks and the second edge blocks. Depth information of non-edge blocks is set according to the depth information of the edge blocks. The depth information of each of the non-edge blocks is associated with depth-filling directions of the neighboring edge blocks, and the depth-filling direction of each of the edge blocks is associated with a similarity between the edge block and a neighboring non-edge block of the edge block. The depth map is generated by using the depth information of the edge blocks and the depth information of the non-edge blocks. 
     In an embodiment of the invention, the system includes a first image sensor, a second image sensor, a memory, and a processor, where the processor is connected to the first image sensor, the second image sensor, and the memory. The first image sensor and the second image sensor are configured to capture images so as to respectively generate a first original image and a second original image. The memory is configured to store data. The processor is configured to: obtain the first original image and the second original image and obtain first edge blocks corresponding to the first original image and second edge blocks corresponding to the second original image; generate depth information of edge blocks according to the first edge blocks and the second edge blocks; set depth information of non-edge blocks according to the depth information of the edge blocks, where the depth information of each of the non-edge blocks is associated with depth-filling directions of the neighboring edge blocks, and the depth-filling direction of each of the edge blocks is associated with a similarity between the edge block and a neighboring non-edge block of the edge block; and generate the depth map by using the depth information of the edge blocks and the depth information of the non-edge blocks. 
     In an embodiment of the invention, the image processing device includes a memory and a processor, where the processor is connected to the memory. The memory is configured to store data. A communication interface is configured to allow the image processing device to be connected to the first image sensor and the second image sensor. The processor is configured to: obtain the first original image and the second original image and obtain first edge blocks corresponding to the first original image and second edge blocks corresponding to the second original image; generate depth information of edge blocks according to the first edge blocks and the second edge blocks; set depth information of non-edge blocks according to the depth information of the edge blocks, where the depth information of each of the non-edge blocks is associated with depth-filling directions of the neighboring edge blocks, and the depth-filling direction of each of the edge blocks is associated with a similarity between the edge block and a neighboring non-edge block of the edge block; and generate the depth map by using the depth information of the edge blocks and the depth information of the non-edge blocks. 
     To make the aforementioned more comprehensible, several embodiments accompanied with drawings are described in detail as follows. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the disclosure and, together with the description, serve to explain the principles of the disclosure. 
         FIG. 1  is a block diagram illustrating a system for generating a depth map according to an embodiment of the invention. 
         FIG. 2  is a flowchart illustrating a method of generating a depth map according to an embodiment of the invention. 
         FIG. 3  is a schematic diagram illustrating an edge block and a depth-filling direction thereof according to an embodiment of the invention. 
         FIG. 4  is a flowchart illustrating a method of setting depth information of non-edge blocks according to an embodiment of the invention. 
         FIG. 5A  is a schematic diagram illustrating an original image according to an embodiment of the invention. 
         FIG. 5B  is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention. 
         FIG. 5C  is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention. 
         FIG. 5D  is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Several embodiments of the invention are described in detail below accompanying with figures. In terms of the reference numerals used in the following descriptions, the same reference numerals in different figures should be considered as the same or the like elements. The embodiments are only a portion of the invention, which do not present all embodiments of the invention. To be more specifically, the embodiments serves as examples of the method, the image processing device, and the system fall within the scope of the claims of the invention. 
       FIG. 1  is a block diagram illustrating a system for generating a depth map according to an embodiment of the invention. It should be noted that the illustrations are provided to make the description more comprehensible and are not intended to limit the invention. All components and positional relationships among the components in the system are described in  FIG. 1  first, and description of functions of the components is later disclosed in detail with reference to  FIG. 2 . 
     With reference to  FIG. 1 , a system  100  includes a first image sensor  110 , a second image sensor  120 , a memory  130 , and a processor  140 . In this embodiment, the system  100  may be an all-in-one image capturing device integrated with the first image sensor  110 , the second image sensor  120 , the memory  130 , and the processor  140  such as a dual-lens digital camera, a single lens reflex camera, a digital video camcorder, a smart phone, a tablet PC, and the like. 
     In the present embodiment, the first image sensor  110  and the second image sensor  120  are photographing lenses including lenses and photosensitive devices. The photosensitive devices are configured to sense intensity of lights entering into the lenses and thereby produce images. The photosensitive devices may be, for example, charge coupled devices (CCDs), complementary metal-oxide semiconductor (CMOS) devices, or other devices. Images captured by the lenses are imaged on sensing devices and are converted into digital signals to be transmitted to the processor  140 . 
     The memory  130  is configured to store data such as images and program codes and may be, for example, a fixed or movable random access memory (RAM) in any form, a read-only memory (ROM), a flash memory, a hard disc or other similar devices, and an integrated circuit and a combination thereof. 
     The processor  140  is configured for controlling operations among the components in the system  100  and may be, for example, a central processing unit (CPU), a graphic processing unit (GPU), a programmable microprocessor for general or special use, a digital signal processor (DSP), a programmable controller, an application specific integrated circuit (ASIC), a programmable logic device (PLD), any other similar device, or a combination of the foregoing devices. 
     Note that in another embodiment, the memory  130  and the processor  140  may be included in personal computers, notebook computers, smart phones, tablet computers, and other electronic devices with image processing functions and receive images of a specific scene captured by the first image sensor  110  and the second image sensor  120  from different angles in a wired or wireless manner through a communication interface (not shown) so as to generate the depth map. In this embodiment, the first image sensor  110  and the second image sensor  120  may be disposed in a same device or may be disposed in different devices. The invention is not limited in this regard. 
     An embodiment is provided hereinafter to elaborate steps of generating a depth map by the system  100  in detail. In the following embodiment, the system  100  is implemented as an image capturing device with dual lenses for illustrative purposes. 
       FIG. 2  is a flowchart illustrating a method of generating a depth map according to an embodiment of the invention. 
     With reference to  FIG. 1  and  FIG. 2  together, first, the processor  140  obtains a first original image and a second original image (Step S 202 ). To be specific, the processor  140  may capture images of a specific scene through the first image sensor  110  and the second image sensor  120  to respectively generate the first original image and the second original image. Hence, the first original image and the second original image are two images captured from a same scene from different angles of view. The first image sensor  110  and the second image sensor  120  may capture the images by using same photographing parameters, and yet the invention is not limited thereto. 
     Next, the processor  140  obtains first edge blocks corresponding to the first original image and second edge blocks corresponding to the second original image (Step S 204 ). Herein, the first edge blocks and the second edge blocks are blocks having edge information respectively in the first original image and the second original image. To be specific, the processor  140  may perform edge detection on the first original image and the second original image so as to detect the first edge blocks and the second edge blocks respectively from the first original image and the second original image. The edge detection is an important step in computer vision. Such step is able to filter out edges with different characteristics through different types of filters so as to identify a boundary of an object in an image. Since the image capturing device with dual lenses is unable to obtain depth information of horizontal edges, the horizontal edges may be removed herein for convenience sake. 
     In an embodiment, the processor  140  may perform edge detection on the first original image and the second original image by using a vertical edge detection filter, so as to detect the vertical first edge blocks and the vertical second edge blocks respectively from the first original image and the second original image. The vertical edge detection filter may be a vertical Sobel operator Sby which is able to obtain vertical edge information directly from the two original images, where: 
     
       
         
           
             Sby 
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     In an embodiment, the processor  140  may perform edge detection on the first original image and the second original image by using an omnidirectional edge detection filter, so as to detect first omni-edge blocks and the second omni-edge blocks respectively from the first original image and the second original image. The processor  140  may further perform edge detection on the first original image and the second original image by using a horizontal edge detection filter, so as to detect first horizontal edge blocks and second horizontal edge blocks respectively from the first original image and the second original image. Afterwards, the processor  140  may perform subtraction on the first omni-edge blocks and the first horizontal edge blocks for generating the first edge blocks and performs subtraction on the second omni-edge blocks and the second horizontal edge blocks for generating the second edge blocks. The omnidirectional edge detection filter may be a Laplacian operator L, where: 
             L   =     (           -   1           -   1           -   1               -   1         8         -   1               -   1           -   1           -   1           )           
The horizontal edge detection filter may be a horizontal Sobel operator Sbx, where:
 
     
       
         
           
             Sbx 
             = 
             
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     Next, the processor  140  generates depth information of edge blocks according to the first edge blocks and the second edge blocks (Step S 206 ). In other words, the processor  140  may obtain the depth information of the edge blocks by performing stereo matching first according to the edge blocks appearing in both original images at the same time by leveraging a depth search algorithm. As for the edge blocks appearing in only one original image (i.e., the edge blocks are obstructed in the other original image), depth information of such edge blocks are estimated by using the steps as follows. 
     Next, the processor  140  sets depth information of non-edge blocks according to the depth information of the edge blocks (Step S 208 ). Herein, the processor  140  may estimate the depth information of the non-edge blocks according to the obtained depth information of the edge blocks with reference to at least one of the original images. The processor  140  may estimate the depth information of each of the non-edge blocks according to a depth-filling direction of a neighboring edge block of the non-edge block, where the depth-filling direction of the edge block is a similarity between the edge block and a neighboring block. 
     Specifically,  FIG. 3 , which is a schematic diagram illustrating an edge block and a depth-filling direction thereof according to an embodiment of the invention, is taken as an example, where S 1  is an object captured in the original images. Since an edge block E 1  belongs to the object S 1 , that is, the edge block E 1  is more similar to a right block R 1  in color, a depth-filling direction of the edge block E 1  is “right”. Note that in the present embodiment, a block with n×m pixels (e.g., 9×9 pixels) in the object S 1  is compared to determine whether the edge block E 1  belongs to the object S 1  so that misjudgment caused by using a single pixel for determination is prevented. Nevertheless, in other embodiments, a single pixel in the object S 1  may be used for comparison. The invention is not limited in this regard. Similarly, since an edge block E 3  belongs to the object S 1  as well, that is, the edge block E 3  is more similar to a left block L 3  in color, a depth-filling direction of the edge block E 3  is “left”. From another perspective, S is a single feature such as a character, a pattern, etc. captured in the original images and is regarded as an edge block E 2  herein. A depth-filling direction of the edge block E 2  is “null”. 
     Accordingly, when processing each of the non-edge blocks, the processor  140  may first obtain depth-filling directions of a left edge block and a right edge blocks closest to the non-edge block among the edge blocks and then set depth information of the non-edge block according to the depth-filling direction of the left edge block and the depth-filling direction of the right edge block. Taking  FIG. 3  for example, a block R 1  is a non-edge block, and the processor  140  sets depth information of the block R 1  according to the depth-filling directions of the left edge block E 1  and the right edge block E 3  closest to the block R 1 . A method of setting the depth information of the non-edge blocks is to be described in detail in the following embodiments. 
     With reference to  FIG. 2  again, afterwards, the processor  140  generates the depth map by using the depth information of the edge blocks and the depth information of the non-edge blocks (Step S 210 ). That is, the processor  140  may estimate depth information corresponding to an object having less features by using more accurate depth information obtained by calculating an object having more features in the specific scene, so as to reduce noise signals. In this way, a more accurate depth estimation would be achieved in a more efficient fashion, and the performance of subsequent stereo vision applications would be thereby enhanced. 
     For ease of description,  FIG. 4 , which is a flowchart illustrating a method of setting depth information of non-edge blocks according to an embodiment of the invention, is used to specifically describe implementations and implementation details of Step S 208  and Step S 210  in  FIG. 2 , and the flowchart of  FIG. 4  may also be implemented by the system  100 . 
     Before the steps of  FIG. 4  are performed, processor  140  has already obtained the first original image, the second original image, and the depth information of the edge blocks. The processor  140  sets at least one of the first original image and the second original image as an image to be used in the flowchart of  FIG. 4 , and the image is referred to as an “original image” hereinafter. 
     With reference to  FIG. 4 , after obtaining an original image Img 0  and depth information BD of the edge blocks, the processor  140  performs a depth estimation by processing each of the non-edge blocks (Step S 400 ). In this embodiment, the processor  140  may sequentially process each of the non-edge blocks of the original image according to an order of left to right and up to down, but the invention is not limited thereto. In the following description, the non-edge block that the processor  140  is processing is defined as a “current non-edge block”. Next, the processor  140  obtains a left edge block and a right edge block of the current non-edge block (Step S 402 ) and determines a depth-filling direction of the left edge block and a depth-filling direction of the right edge block (Step S 404 ). 
     Specifically,  FIG. 5A , which is a schematic diagram illustrating an original image Img 0  according to an embodiment of the invention, is taken as an example, and (0, 0), (x_bond, 0), (0, y_bond), and (x_bond, y_bond) are coordinates of four end points of the original image Img 0 . It is assumed that the processor  140  is processing a pixel row ycnt=y0 and obtains a leftmost edge block L_edge corresponding to an object S 5 . The leftmost edge block L_edge acts as the left edge block, and (x0, y0) are the coordinates of the left edge block L_edge. Next, the processor  140  searches for a next edge block R_edge to a right side of the same pixel row ycnt=y0. The edge block R_edge acts as the right edge block, and (xcnt, y0) are the coordinates of the right edge block R_edge. All pixels located between the left edge block L_edge and the right edge block R_edge in the pixel row ycnt=y0 are then regarded as the current non-edge block by the processor  140 . 
     Herein, the processor  140  first determines color similarities between the left edge block L_edge and a left block and a right block. The color similarity between the left edge block L_edge and the right block is determined to be high herein, and thereby, a depth-filling direction of the left edge block L_edge is set to be “right” and may be recorded as “+1”. Next, the processor  140  determines color similarities between the right edge block R_edge and a left block and a right block. The color similarity between the right edge block R_edge and the left block is determined to be high herein, and thereby, a depth-filling direction of the right edge block R_edge is set to be “left” and may be recorded as “−1”. As a side note, if the processor  140  determines that the color similarities between the right edge block R_edge and the left block and the right block are both not high or determines that the color similarities between the right edge block R_edge and the left block and the right block are both high (e.g., one of the left block and the right block is set to be “+1, and the other one is set to be “−1”), the depth-filling direction is “null” and is recorded as “0” by the processor  140 . Herein, the comparison of color similarity between two blocks is made by determining whether a difference value between pixel values of the two blocks is less than a threshold. When the difference value is less than the threshold, the color similarity is determined to be high, and on the contrary, the color similarity is determined to be low. 
     Next, the processor  140  sets depth information of the current non-edge block according to depth-filling directions of a left edge block and a right edge block of the current non-edge block. First, the processor  140  performs a switch (SW) so as to determine if any of four conditions C 1  to C 4  is satisfied. 
     When entering the condition C 1 , the processor  140  determines that the depth-filling direction of the left edge block is “right” and the depth-filling direction of the right edge block is “left”, and it means that the left edge block and the right edge block both correspond to the same object. Hence, the processor  140  sets the depth information of the current non-edge block according to a linear interpolation method for continuity purposes. For instance, it is assumed that a depth value of the left edge block is 1, a depth value of the right edge block is 5, and the current non-edge block occupies 3 pixels. After the linear interpolation method is performed, pixel values of the current non-edge block are 2, 3, and 4. 
     When entering the condition C 2 , the processor  140  determines that the depth-filling direction of the left edge block is “right” and the depth-filling direction of the right edge block is “right” or “null”. It means that the left edge block and the right edge block correspond to different objects, and thus the depth information is discontinuous. Herein, since the depth-filling direction of the left edge block is “right”, the left edge block and the current non-edge block belong to the same object. The processor  140  thus sets the depth information of the current non-edge block by copying the depth information of the left edge block. For instance, it is assumed that the depth value of the left edge block is 1, the depth value of the right edge block is 5, and the current non-edge block occupies 3 pixels. After copying is performed, the pixel values of the current non-edge block are 1, 1, and 1. 
     On the other hand, when entering the condition C 3 , the processor  140  determines that the depth-filling direction of the left edge block is “left” or “null” and the depth-filling direction of the right edge block is “left”. It means that the left edge block and the right edge block correspond to different objects, and the depth information is discontinuous. Herein, since the depth-filling direction of the right edge block is “left”, the right edge block and the current non-edge block belong to the same object. The processor  140  thus sets the depth information of the current non-edge block by copying the depth information of the right edge block. For instance, it is assumed that the depth value of the left edge block is 1, the depth value of the right edge block is 5, and the current non-edge block occupies 3 pixels. After copying is performed, the pixel values of the current non-edge block are 5, 5, and 5. 
     To be specific,  FIG. 5B , which is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention, is taken as an example, and S 51  to S 57  belong to five different objects. Left arrows and right arrows are respectively used to indicate the depth-filling directions of the edge blocks to be in the left direction and the right direction, and the depth-filling direction of the “null” direction is not shown. Herein, the processor  140  sets the depth information of the non-edge block between the left edge block with the depth-filling direction of “right” and the right edge block with the depth-filling direction of “left” through a linear interpolation method LI. In addition, the processor  140  sets the depth information of the non-edge block between the left edge block with the depth-filling direction of “right” and the right edge block with the depth-filling direction of “right” or “null” or between the left edge block with the depth-filling direction of “left” or “null” and the right edge block with the depth-filling direction of “left” through a copying method CP. 
     With reference back to  FIG. 4 , when entering the condition C 4 , the processor  140  determines that the depth-filling direction of the left edge block is “left” or “null” and the depth-filling direction of the right edge block is “right” or “null”. It means that the left edge block and the right edge block correspond to different objects, and it also means that the current non-edge block, the left edge block, and the right edge block all corresponds to different objects. Herein, the processor  140  obtains the left edge block, the current non-edge block, and an upper block of the right edge block, where the upper block is a pixel row located right above the left edge block, the current non-edge block, and the right edge block. Taking  FIG. 5A  for example, the upper block may be expressed as ([x0:xcnt], y0−1), meaning that the upper block includes pixels of and between (x0, y0−1) and (xcnt, y0−1). The processor  140  determines whether similarity between colors of the current non-edge block and the upper block is high and whether the upper block has depth information. If yes, the processor  140  then sets the depth information of the current non-edge block by copying the depth information of the upper block. 
     To be specific,  FIG. 5C , which is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention, is taken as an example. The processor  140  sets the depth information of the non-edge block between the left edge block with the depth-filling direction of “left” or “null” and the right edge block with the depth-filling direction of “right” or “null” by copying an upper block CP′. 
     With reference to  FIG. 4  again, after the processor  140  enters the condition C 1 , the condition C 2 , or the condition C 3  and obtains the depth information of the current non-edge block, Step S 406  is performed. The processor  140  determines whether the similarity between the colors of the current non-edge block and the upper block is high and whether the upper block has depth information. If the upper block does not have any depth information, the processor  140  sets the depth information of the upper block according to the depth information of the current non-edge block based on a floor filling method.  FIG. 5D , which is a schematic diagram illustrating a method of setting depth information according to an embodiment of the invention, is taken as an example. After obtaining depth information of a non-edge block N 1  and determining a non-edge block N 2  lacks depth information, the processor  140  sets the depth information of the non-edge block N 2  as the depth information of the non-edge block N 1  through a floor filling method FL. 
     Next, the processor  140  determines whether all of the non-edge blocks are processed (Step S 408 ). If no, the processor  140  sets the next non-edge block to be processed as the current non-edge block, and Step S 402  is then performed again. If yes, it means that all of the non-edge blocks are processed by the processor  140 , and setting of the depth information of the non-edge blocks is completed. Hence, the depth information of the edge blocks and the non-edge blocks is outputted (Step S 410 ) to generate the depth map of the specific scene. 
     In view of the foregoing, in the method, the image processing device, and the system for generating the depth map, the depth information corresponding to blocks with no edge information is estimated by using more precise depth information calculated based on obtained through calculating blocks with edge information in a specific scene, so as to reduce noise signals and to achieve a more accurate depth estimation. Therefore, the effectiveness of stereo vision application such as structured light, stereo, distance detection, and surveillance would be greatly enhanced. 
     It will be apparent to those skilled in the art that various modifications and variations can be made to the disclosed embodiments without departing from the scope or spirit of the disclosure. In view of the foregoing, it is intended that the disclosure covers modifications and variations provided that they fall within the scope of the following claims and their equivalents.