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Tham khảo tài liệu 'advances in theory and applications of stereo vision part 13', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 290 Advances in Theory and Applications of Stereo Vision Image name Number of declivities color declivities Barnl 8446 12177 Cones 8538 12880 Teddy 8710 11733 Tsukuba 7216 10214 Table 1. Number of color declivities extracted in color images compared to number declivities extracted in corresponding gray level image Fig. 8. Pixels of adjacent different colored objects with strictly monotonous gray level values. a color image. b color declivity image. c the corresponding gray level image of a . d declivity image. a b c Fig. 9. Metamerism phenomena. Colors which reflect the same amount of light. Colors for gray level values equal to a 200 b 127 and c 50. 3. Color matching 3.1 State of the art Introduction of different stereo correspondence algorithms can be found in the survey by Scharstern and Szeliski Scharstein Szeliski 2002 and the one by Brown et al. Brown Hager 2003 . Matching approaches can be divided into local and global methods depending on their optimization strategy Brown Hager 2003 . 3.1.1 Local methods Local methods can be very efficient but they are sensitive to locally ambiguous regions in images. They fall into three categories Block matching Banks Corke 2001 Search for maximum match score or minimum error over small region typically using variants of cross-correlation or robust rank metrics. These methods are very suitable for dense matching and conceivable in realtime. We have a correct matching in the case of a light vertical displacement between New Robust Obstacle Detection System using Color Stereo Vision 291 stereoscopic pair. These algorithms always provide a matching result even in the case of an occlusion which implicates a false matching. They are also little accurate on zones with not enough textures and sensitive to depth discontinuity. Gradient methods Twardowski et al. 2004 Minimize a functional typically the sum of squared differences over a small region. These methods has a correct matching in the case of a light vertical displacement
