*Result*: Fast Shape Retrieval Based on Differential Chain Code Descriptor and Fuzzy Contour Matching.

*To address the issues of slow processing, poor robustness, and performance degradation in complex scenarios often seen in traditional image matching methods, a fast contour matching approach based on differential chain codes is proposed. This method leverages the structural and topological information inherent in object contours by encoding contour curves into directional differential chain code sequences, effectively transforming contour matching into a highly efficient sequence comparison problem. During the matching process, a segmented contour matching strategy is adopted, dividing the overall contour into smaller segments for individual matching. A robust verification mechanism is introduced to reduce the risk of mismatches caused by noise interference. Extensive experiments on both synthetic and real-world datasets demonstrate that the proposed method significantly improves processing speed while maintaining high matching accuracy. Moreover, it shows strong stability and robustness under challenging conditions, such as noise, blur, and occlusion. This algorithm has great potential for real-time applications in areas such as robotic perception, industrial visual inspection, and mobile vision systems. [ABSTRACT FROM AUTHOR]

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