Fast Parallel Thinning Algorithm

This document introduces a fast parallel thinning algorithm designed for curve data processing with guaranteed connectivity preservation in the refined results. The algorithm achieves high-speed performance through parallel processing techniques, enabling efficient handling of large-scale curve datasets. Key implementation features include iterative pixel classification using connectivity-preserving templates and parallel computation optimization that allows simultaneous processing of multiple curve segments. Applications span various domains including computer graphics (for vectorization and skeleton extraction) and medical image processing (for vascular network analysis and feature enhancement). The algorithm employs neighborhood operation patterns and connectivity checks to maintain topological integrity during thinning operations. We believe this algorithm can significantly enhance your workflow efficiency. For technical inquiries regarding implementation details (such as template design or parallelization strategies) or additional support, please contact our team.