Towards automatic visual obstacle avoidance
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Parametric correspondence and chamfer matching: two new techniques for image matching
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
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This paper describes an approach to object recognition in textured images. The method is based on image matching via the distance transform. The proposed matching scheme is an extension and combination of the conventional methods used in image processing. Interesting points are detected to replace edge pixels as image feature pixels in the distance transform for the matching measurement. A mask based stochastic method is introduced to extract texture features. The detection of interesting points for matching is then performed on the texture feature image, named the texture energy image. A dynamic thresholding procedure is further applied to guide the matching. Our experimental results demonstrate that the combination of texture feature extraction and interesting points detection provides a better solution to the search for the best matching between two textured images. In addition, such an algorithm is simple to implement and quite insensitive to noise and other disturbances.