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Real-Time Disparity Map Generation for Stereo Vision Based Obstacle

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Real-Time Disparity Map Generation for Stereo Vision Based Obstacle International Journal of Pure and Applied Mathematics Volume 119 No. 12 2018, 14501-14507 ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu Real-Time Disparity Map Generation For Stereo vision Based Obstacle Detection System Using SAD Algorithm David Rajkumar Jayakumar M.Tech in Remote Sensing and GIS, Developer - Proprocure London, United Kingdom E-mail:[email protected] Abstract—Stereo vision sensor captures images to navigate the The closer the object is to the observer, the greater that autonomous ground vehicle by visual perception of the environment. difference in position. Anybody can see this for oneself by Stereo-vision is the ability to infer information about the 3-D holding up a finger in front of his or her face and closing one structure of a scene using two images captured simultaneously by two eye. Line the finger up with any object in the distance. Then different imaging sensors at different viewpoints. Disparity estimation is the process of computing the relative depth of objects switch eyes and watch the finger. within a scene. The disparity map for the two images captured by A. Geometry stereo vision camera is generated to compute the range of the obstacle. On identification of the obstacle the vehicle decides which An artificial stereo vision system uses two cameras at two path to navigate. This paper presents a methodology for real-time known positions. Both cameras take a picture of the scene at multi-resolution disparity map generation for stereo vision based the same time. Using the geometry of the cameras, the obstacle detection system. geometry of the environment can be computed. As in the biological system, the closer the object is to the cameras, the Keywords—stereo vision; disparity; range estimation; digital image processing; sum of absolute differences algorithm; greater its difference in position in the two pictures taken with those cameras. The measure of that distance is called the I. INTRODUCTION disparity. Stereovision system can theoretically yield an accurate and detailed 3D representation of the environment around a vehicle, with a passive sensor at relatively low cost. Disparity map is generated to calculate the range or the depth factor. Capturing a scene(left and right images) from two point of view at the same time, stereo techniques aim at defining conjugate pairs of pixels, one in each image, that correspond to the same spatial point in the scene. The difference between positions of conjugate pixels, called the disparity, yields the depth of the point in the 3D scene. The disparity map is generated using Sum of Absolute Difference(SAD) algorithm. II. STEREO VISION Fig 1. Geometry of stereo vision Stereoscopy, stereoscopic imaging or 3D (three- The distance f is the perpendicular distance from each dimensional) imaging is any technique capable of recording focal point to its corresponding image plane. Point P is some three-dimensional visual information or creating the illusion of point in space which appears in the images taken by these depth in an image. The illusion of depth in a photograph, cameras. Point P has coordinates (x, y, z) measured with movie, or other two-dimensional image is created by respect to a reference frame that is fixed to the two cameras presenting a slightly different image to each eye. Stereoscopy and whose origin is at the midpoint of the line connecting the is useful in viewing images rendered from large multi- focal points. The projection of point P is shown as Pr in the dimensional data sets such as are produced by experimental right image and Pl in the left image and the coordinates of data[5]. The three-dimensional depth information can be these points are written as (x , y ) and (x , y ) in terms of the reconstructed from two images using a computer by the r r l l image plane coordinate systems shown in the figure. Note that corresponding the pixels in the left and right images. Solving the disparity defined above is x - x . Using simple geometry, the Correspondence problem in the field of Computer Vision l r aims to create meaningful depth information from two images. Artificial stereo vision is based on the same principles as biological stereo vision. A perfect example of stereo vision is the human visual system. Each person has two eyes that see two slightly different views of the observer’s environment. An object seen by the right eye is in a slightly different position in the observer’s field of view than an object seen by the left eye. 14501 International Journal of Pure and Applied Mathematics Special Issue The distance is inversely proportional to disparity and that C. Image Rectification disparity is directly proportional to the baseline. When Image rectification is a transformation process used to cameras are aligned horizontally, each image shows a project multiple images onto a common image surface. It is horizontal difference, xl - xr, in the location of Pr and Pl, but no used to correct a distorted image into a standard coordinate vertical difference. Each horizontal line in one image has a system. corresponding horizontal line in the other image. These two 1. It is used in computer stereo vision to simplify the matching lines have the same pixels, with a disparity in the problem of finding matching points between location of the pixels. The process of stereo correlation finds images. the matching pixels so that the disparity of each point can be 2. It is used in geographic information systems to known. Note that objects at a great distance will appear to merge images taken from multiple perspectives have no disparity. Since disparity and baseline are into a common map coordinate system. proportional, increasing the baseline will make it possible to Stereo vision uses triangulation based on epipolar geometry detect a disparity in objects that are farther away. However, it to determine distance of an object. Between two cameras there is not always advantageous to increase the baseline because is a problem of finding a corresponding point viewed by one objects that are closer will disappear from the view of one or camera in the image of the other camera. (This is called the both cameras. correspondence problem.)[7] In most camera configurations, finding correspondences requires a search in two dimensions. B. Methodologies However, if the two cameras are aligned to have a common The steps for the range estimation involves: image plane, the search is simplified to one dimension - a line that is parallel to the line between the cameras (the baseline). Image rectification is an equivalent (and more often used) alternative to this precise camera alignment. It transforms the images to make the epipolar lines (epipolar geometry) align horizontally. D. Disparity The measure of difference between positions of pixels is called the disparity. There are two types of disparity. They are Horizontal Disparity and Vertical Disparity. If the two cameras are mounted on a vertically aligned frame then there will be horizontal disparity alone and no vertical disparity[6]. If the two cameras are mounted on a horizontally aligned frame then there will be vertical disparity and no horizontal disparity. The task of developing a stereo vision system presents many issues with both software and hardware. If the system is to be used outdoors, problems with variable lighting and weather are added. A system where the scene in the images is not stationary adds timing issues with respect to image capture. Mounting this system on a robotic platform which traverses a rugged landscape adds vibrations to the system which can sometimes be intense. The stereo vision system must accomplish the following tasks: 1. Capture two images of the scene: This requires two cameras and two camera lenses. This is mostly a hardware issue. Fig 2. Offset of the image 2. Transfer these images to a computer for The figure displays stereo geometry. Two images of the processing: This may be done with capture cards same object are taken from different viewpoints. The distance or some other way of digital data transfer such as between the viewpoints is called the baseline (b). The focal fire wire. This is both hardware and a software length of the lenses is f. The horizontal distance from the issue. image center to the object image is dl for the left image, and dr 3. Process the images for 3D data: This requires for the right image. stereo processing software which may be Normally, the stereo cameras are set up so that their image purchased. planes are embedded within the same plane. Under this Process the 3D data into a traversibility grid: This requires condition, the difference between dl and dr is called the grid computing software which must be written for this task. disparity, and is directly related to the distance r of the object 14502 International Journal of Pure and Applied Mathematics Special Issue normal to the image plane. The relationship is r = b * f / d, Where, d = dl - dr. E. Range Estimation A pixel in the disparity image represents the range of an object. This range, together with the position of the pixel in the image, determines the 3D position of the object. The coordinate system for the 3D image is taken from the optic Fig 4.Epipolar line center of the left camera of the stereo rig. Z is along the optic C. Sum of Absolute Differences axis, with positive Z in front of the camera. X is along the camera scan lines, positive values to the right when looking Disparity map generation algorithm uses a simple along the Z axis. Y is vertical, perpendicular to the scan lines, technique, SAD.
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