Skin Color-Based Face Detection Implementation in MATLAB

This document presents my original MATLAB implementation of a skin color-based face detection algorithm. The code analyzes skin tone characteristics within images to identify human faces. I selected MATLAB as the development environment due to its robust image processing capabilities and flexibility for computer vision applications. Through this project, I gained practical experience in leveraging skin color information for facial detection - a fundamental technique in image processing and computer vision domains.

The implementation incorporates essential image processing techniques including color space conversion (particularly from RGB to HSV/YCbCr color spaces for better skin tone isolation) and adaptive threshold segmentation. Key functions involved color channel extraction, morphological operations for noise reduction, and region property analysis for face candidate validation. Parameter optimization was performed through iterative testing to enhance detection accuracy and computational efficiency, adjusting factors like threshold values and minimum region sizes.

This development process not only advanced my programming proficiency but also provided deep insights into computer vision concepts including color modeling, feature extraction, and object detection methodologies. The code demonstrates practical application of theoretical concepts through histogram analysis of skin tone distributions and connected component processing for face region identification.