Skeleton Extraction Algorithm Using Thinning Method

The skeleton extraction algorithm based on thinning method is an approach used for extracting image skeletons. This algorithm processes test images to achieve satisfactory results, typically implemented through iterative pixel removal while preserving connectivity. Skeleton extraction represents a significant research direction in computer vision, with broad applications in image analysis, pattern recognition, and related fields. The thinning algorithm works by progressively eliminating boundary pixels from binary images while maintaining topological properties, ultimately revealing the essential medial axis structure. Key implementation aspects include connectivity checks, endpoint preservation, and iteration control using functions like morphological operations or specialized thinning kernels. The algorithm's advantage lies in its ability to retain fundamental image characteristics while eliminating redundant information, resulting in clearer and more concise structural representations. Common code implementations involve neighborhood pattern analysis and conditional pixel removal based on connectivity rules. Therefore, the thinning-based skeleton extraction algorithm serves as an efficient image processing technique for structural analysis and feature reduction.