MATLAB-Based Face Recognition Algorithm Implementation

Application Background

Face recognition is a biometric identification technology that authenticates individuals based on facial feature information. The system captures facial images or video streams using cameras or webcams, automatically detects and tracks faces within the images. It then applies a series of facial processing techniques to analyze detected faces. This technology is commonly referred to as portrait recognition or facial recognition. In MATLAB implementations, this typically involves using Computer Vision Toolbox functions like vision.CascadeObjectDetector for face detection and image processing algorithms for feature analysis.

Key Technologies

Face recognition systems primarily consist of four components: face image acquisition and detection, facial image preprocessing, facial feature extraction, and matching/recognition. The feature extraction phase often employs algorithms like PCA (Principal Component Analysis) or LBP (Local Binary Patterns) implemented through MATLAB's pca() function or custom feature extraction code.

Generally, a complete face recognition system includes image capture, face localization, image preprocessing, and face recognition (identity verification or identification search). The system input typically consists of one or multiple unidentified facial images along with a facial database containing known identities. The output generates similarity scores indicating identity matches, which can be computed using distance metrics like Euclidean distance or cosine similarity in MATLAB code. Preprocessing steps commonly involve histogram equalization (histeq() function) and image normalization to enhance recognition accuracy.

Furthermore, practical applications of face recognition technology include security control systems, facial payment authentication, and intelligent access control systems, significantly improving daily convenience and safety. MATLAB implementations often integrate these components through system integration using GUI development or Simulink models for real-time processing applications.