Face Recognition System Using Principal Component Analysis (PCA)
A face recognition system implementation based on Principal Component Analysis (PCA) with algorithm explanations and feature extraction techniques.
Implementation of Face Recognition System Using Principal Component Analysis (PCA)
This system employs 2D PCA algorithm to compute dimension reduction matrix for training set vectors, and utilizes nearest neighbor method to evaluate recognition accuracy on test datasets with code implementation insights.
Implementation of a Face Recognition System Based on 2D-DCT and Modular 2DPCA
MATLAB Implementation of a Face Recognition System Using 2D-DCT and Modular 2DPCA with Code Implementation Details
Face Detection System: MATLAB-based Face Recognition Implementation
MATLAB-implemented face recognition system featuring 9 source code files and hundreds of facial images, demonstrating computer vision algorithms for detection and identification
PCA-Based Face Recognition System Implementation
Complete PCA-based face recognition system implemented in MATLAB with detailed usage documentation. This program demonstrates key computer vision algorithms including eigenface computation, dimensionality reduction, and classification techniques, serving as excellent reference material for pattern recognition studies.
MATLAB Implementation of a Face Recognition System
MATLAB face recognition system, featuring comprehensive code implementation with detailed algorithm descriptions. Download now for efficient and accurate facial identification solutions suitable for various applications including security systems and human-computer interaction interfaces.
MATLAB Code Implementation for Face Recognition System
A comprehensive face recognition system implementation featuring image processing, recognition algorithms, and reconstruction capabilities. Includes detailed code explanations for key functions and processing methods.
FLD-Based Face Recognition System (Fisherface Implementation)
This package implements a Fisher Linear Discriminant (FLD) based face recognition system, known as the Fisherface method. The implementation features heavily commented code with clear function descriptions, including data preprocessing routines, eigenvalue decomposition for optimal projection vectors, and classification algorithms for face matching.
Face Recognition System Based on MATLAB R2008
A face recognition system developed using MATLAB R2008 that implements two distinct algorithms: PCA+Adaboost and PCA+SVM, utilizing the ORL face database. The system achieves 84% recognition accuracy by processing a single facial image to identify individuals, demonstrating efficient feature extraction and classification through principal component analysis combined with ensemble learning and support vector machine methods.
Face Recognition System Implementation in MATLAB
A simple MATLAB-based face recognition system implementation using GUI interface. Execute by running facerecog.fig file, includes FaceDatabase library for facial feature storage and comparison. The system demonstrates basic image processing and pattern recognition techniques through practical implementation.