MATLAB Implementation for Digital Image Processing: Image Skeletonization

This text discusses digital image processing, specifically focusing on an image skeletonization program. Skeletonization is an image processing technique that extracts the main structural framework of an image by eliminating non-essential parts. In this experiment, we implement the medial axis transformation method, which obtains the image skeleton through a series of image processing steps. The program design must consider various aspects of image processing, including algorithm complexity and the accuracy of skeletonization results.

Key implementation aspects include using MATLAB's morphological operations such as bwmorph() with 'skel' parameter for skeletonization, or developing custom algorithms using thinning operations. The medial axis transformation typically involves iterative erosion of binary images while preserving endpoints and connectivity. The algorithm requires careful handling of connectivity rules (4-connectivity or 8-connectivity) and termination conditions to ensure proper skeleton extraction.

Therefore, in this experiment, we need to thoroughly study the principles of skeletonization to better understand and master relevant knowledge in digital image processing, including practical implementation considerations and performance optimization techniques.