Facial, Skin, and Eye Detection with Eye Pattern Matching

Face detection, skin segmentation, and eye pattern recognition are fundamental components in computer vision systems for applications such as facial recognition, emotion analysis, and biometric security. This MATLAB implementation utilizes Haar cascade classifiers for robust face detection, followed by color-based skin segmentation using YCbCr color space to isolate facial regions. For eye detection and pattern matching, the algorithm employs template matching techniques with normalized correlation coefficients to compare eye patterns against reference templates. The code includes preprocessing steps such as histogram equalization for illumination normalization and morphological operations for noise reduction. Key MATLAB functions used in this implementation include vision.CascadeObjectDetector for face detection, rgb2ycbcr for color space conversion, and normxcorr2 for template matching operations. This comprehensive approach ensures accurate detection and matching of facial features while providing a modular framework that can be extended for more complex computer vision applications.