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Stereo matching algorithm based on binocular stereo vision

Author: LiuXiaoQun
Tutor: LuoGuiE
School: Central South University
Course: Electronic Science and Technology
Keywords: Binocular stereo vision Image preprocessing Stereo matching Performance Evaluation
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 357
Quote: 2
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Binocular vision is to mimic the human binocular function of the same scene from two different angles of observation, derived according to the principle of geometrical imaging parallax between the images of the acquired image and then under different angles, so as to restore the three-dimensional information of the scene. Stereo matching process is the search for an image of the same name in the imaging process and get the image deviation, is the core technology of three-dimensional reconstruction, three-dimensional visual focus on content, is also one of the difficulties. The image preprocessing binocular stereo matching algorithms can be achieved, the VC platform optimal algorithm for image on a grayscale conversion, smoothing and sharpening pretreatment for stereo matching and lay a solid foundation. Stereo matching algorithm, the research and the improvement of the regional matching algorithm and feature matching algorithm. The subject of the window fixed window area matching algorithm to improve regional matching algorithm based on the disparity gradient. This algorithm introduces a new similarity measure function the SAD function instead of the traditional, to match the different regions with different window sizes on the basis of the disparity gradient theory, this can reduce the search range, and reduce the false match rate. Feature matching algorithm for classic Harris corner feature matching algorithm sensitive to image scale changes shortcomings, an improved scale invariant feature-based Harris corner feature matching algorithm, this algorithm first detection operator be improved so that it has a scale-invariant feature, then the introduction of the most stable performance in the feature vector generating process descriptor so that it can improve the stability of the match. Finally, analysis of the advantages and disadvantages of the first two algorithms, according to the complementary strategy, proposed a region and characterized in the combination of matching algorithm, The algorithm according to the principle of the parallax gradient on the basis of the edge extraction, edge region of the subject improved Harris detection operator to extract the corner and then matching feature points, then the image of feature matching subjects improved regional matching algorithm to match, this would both reduce the search range and improve the speed of matching region matching can also be obtained dense disparity map matching the correct rate. The algorithm uses a subject in the standard image in both qualitative and quantitative aspects of the comparison results show that the correct rate of the region and characterized in the combination of matching algorithm is higher, the performance is also more stable.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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