Abstract
A new algorithm called Fuzzy Randomized Generalized Hough Transform (FRGHT) was proposed to improve the industrial detection accuracy and the speed of image matching in this paper. This algorithm combined Fuzzy Inference System (FIS) and Random Generalized Hough Transform (RGHT), in which fuzzy sets of FIS were used to compute the votes of edge points of reference image for registration parameters, can effectively solve the problem of noise and distortion and improves the matching accuracy; and the random sampling giving a many-to-one mapping reduces the memory requirements and improves the matching speed. The experiments demonstrate that the proposed algorithm exhibits faster speed and higher accuracy than RGHT and Fuzzy GHT (FGHT), moreover it is robust to the serious noise pollution, distortion, occlusions, clutter, etc.
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