Extraction of Image Skeleton Structure

This MATLAB implementation provides a clear and accessible method for extracting skeleton structures from images, complete with illustrative examples for reference. The approach enables users to intuitively understand and master the image skeletonization process. Our implementation utilizes morphological operations - primarily through MATLAB's bwmorph function with the 'thin' parameter - which iteratively erodes boundary pixels while preserving connectivity until only the central skeletal structure remains. In the provided example, we demonstrate how to extract skeletal features from an input image, allowing users to clearly visualize the primary structural components. The method involves preprocessing steps such as image binarization using graythresh and imbinarize functions, followed by skeletonization algorithms that maintain topological properties while reducing shapes to their medial axes. This technique enables rapid and accurate acquisition of image skeletons, which can be effectively applied in subsequent image processing and analysis tasks across various domains including pattern recognition, medical imaging, and computer vision. The implementation includes error handling for image input validation and parameter optimization guidance for different image types. We believe this method will prove valuable for your image processing workflow!