MATLAB Implementation of Face Recognition with Gabor Filtering and Neural Network Training
A face recognition program implementing Gabor filtering for feature extraction and neural network training for classification
MATLAB Implementation of Gabor Filter for Edge Detection and Texture Analysis
Application Background: Gabor filter serves as a linear filter for edge detection in image processing, with frequency and directional responses similar to the human visual system. Research shows Gabor filters excel in texture representation and separation, consisting of Gaussian kernel functions modulated by sinusoidal plane waves in the spatial domain. Technical Approach: Comparative analysis of PCA dimensionality reduction examples reveals consistent methodology - extracting covariance matrices from original data, computing eigenvectors/eigenvalues, and generating transformation matrices through KL transformation based on eigenvalue-sorted eigenvectors.
MATLAB-Based Fingerprint Recognition System
A fingerprint recognition program implemented in MATLAB that performs Gabor filtering, binarization, erosion and other preprocessing operations on fingerprint images, utilizing SVM algorithms to determine whether new fingerprint images exist in the original database. Suitable for demonstrating small-scale fingerprint identification systems with detailed implementation approaches for image processing and machine learning components.
Gabor Filtering for Image Denoising
Gabor Filter Denoising Technique with Code Implementation Details
Core Functionality of Gabor Filter Implementation
MATLAB-based implementation of Gabor filter core features with parameter optimization for texture analysis
Complete Fingerprint Recognition System
This comprehensive fingerprint recognition program implements key processing stages including histogram equalization, Gabor filter-based image enhancement, orientation field filtering, ridge thinning, feature extraction, and feature matching. The system incorporates three distinct matching algorithms and includes supplementary presentation materials detailing implementation approaches, making it highly valuable for research and study.