Face Recognition Implementation in MATLAB Code
MATLAB-based face recognition system - simply run TEST.m to see results. This implementation detects faces in images/videos and annotates them with bounding boxes using computer vision algorithms.
Face Recognition Using Feature Matrix Method with MATLAB Implementation
MATLAB source code for face recognition implementing the feature matrix approach, including sample images and test datasets. The image filenames correspond directly to the naming conventions used in the MATLAB code. After extracting the compressed archive, the source code can be executed immediately without additional configuration.
Neural Network-Based Face Recognition Training Function
Face recognition training function using neural networks, highly practical implementation from excellent postgraduate research projects
NMFs Algorithm (Non-negative Matrix Factorization with Sparsity Constraint)
The NMFs algorithm (Non-negative Matrix Factorization with Sparsity Constraint) implements face recognition based on local facial features through approximate matrix decomposition for spatial dimensionality reduction, optimizing sparse component extraction using regularization techniques.
Gabor 2DPCA Face Recognition Algorithm
A custom-implemented Gabor 2DPCA face recognition algorithm that extracts Gabor features and performs recognition using 2DPCA. Tested on the Yale face database with high accuracy and fast processing speed. The code allows direct recognition rate output by simply adjusting the number of training samples. Includes pre-loaded Yale database for immediate execution and result visualization - implements Gabor filter convolution, 2DPCA dimensionality reduction, and classification modules.
NMF Decomposition for Face Recognition with MATLAB Implementation
MATLAB-based NMF decomposition program for face recognition applications, featuring multiple algorithmic implementations
Gabor Wavelet Face Recognition with Feature Extraction and Dimensionality Reduction
Gabor wavelet-based face recognition system utilizing LBP feature extraction, PCA, and LPP dimensionality reduction. A graduation project focusing on algorithm implementation for optimized facial recognition under challenging conditions.
MATLAB-Based Facial Image Attendance System
This project implements a facial recognition system using MATLAB. Unlike traditional approaches that perform simple head-to-head comparisons with limited practical value, this system employs an innovative methodology. The recognition process involves capturing facial data for training to extract unique facial features. During testing, the system processes full upper-body or full-body images by detecting and isolating faces, performing dimensionality reduction, and comparing them against a database. The system outputs identified individuals with their personal information while tracking attendance records. The architecture also supports secondary development for recognizing unknown faces outside the database, enabling alarm-triggering functionality for enhanced security.
Source Code for SRC Face Recognition
Sparse Representation Classifier implementation for face recognition applications, featuring well-documented function code suitable for beginners. Includes detailed algorithm explanations and practical implementation examples.
Image Preprocessing for Face Recognition
Commercial Image Processing for Illumination Reduction - Image Preprocessing Suitable for Face Recognition Applications