Image Thinning Algorithm Based on MATLAB Implementation

The MATLAB-based image thinning algorithm is a method for extracting fine structures from digital images. This algorithm utilizes MATLAB's image processing toolbox to implement skeletonization through a series of morphological operations. The implementation typically involves iterative thinning procedures using structuring elements and logical operations to preserve connectivity while removing redundant pixels. Common approaches include Zhang-Suen thinning algorithm or medial axis transform, which can be coded using MATLAB functions like bwmorph, imerode, and logical indexing. This thinning technique finds applications in computer vision, image analysis, and pattern recognition systems. By employing this algorithm, researchers can better analyze and understand detailed structural information in images, enabling more advanced research and practical applications in feature extraction and object recognition. The code implementation usually includes preprocessing steps like binarization, followed by iterative thinning cycles that remove boundary pixels while maintaining topological properties.