A New Corner Matching Algorithm using Fuzzy Relational Approach

A. Kar, A. Dutta, and B.N. Chatterji (India)


corner matching, fuzzy relations


Corner matching in image sequences is an important and difficult problem that serves as a building block of several important applications of stereo vision etc. In this paper, we use a similarity measure based on fuzzy relation in order to establish the corner correspondence between two images in the presence of intensity variations and motion blur. The matching approach proposed by us needs only to extract one set of corner points as candidates from the first frame, and the positions of which in the second frame are determined by matching, not by extracting. Experiments conducted with the help of various sequences of images prove the superiority of our algorithm over standard and zero mean cross correlation as well as one contemporary work using mutual information as a window similarity measure combined with graph matching techniques under non-ideal conditions.

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