Color Image Skin Region Segmentation Algorithm

This paper presents a MATLAB-based color image skin region segmentation algorithm that effectively partitions images for enhanced processing and analysis. We provide detailed explanations of the algorithm's underlying principles and implementation process, supported by experimental validation. Specifically, the study begins with an introduction to the fundamental concepts and processing workflow, then elaborates on the practical implementation methods for each step using MATLAB's image processing toolbox. The algorithm employs color space transformation (typically RGB to YCbCr or HSV) and threshold-based segmentation techniques, where skin tone distributions are modeled through histogram analysis and probability mapping. Multiple experimental datasets demonstrate the algorithm's effectiveness and stability in various lighting conditions and skin tones. Additionally, we analyze the algorithm's strengths and limitations, suggesting potential improvements such as adaptive thresholding, morphological operations for noise reduction, and machine learning approaches for enhanced accuracy. The implementation includes key functions like imread for image loading, rgb2ycbcr for color conversion, and regionprops for blob analysis to refine segmentation results.