Image Retrieval Using Harris Interest Points
An image retrieval system based on Harris interest points featuring comprehensive implementation including feature extraction, feature matching algorithms, and result return mechanisms.
Principal Component Analysis: Extracting Key Features for Signal Reconstruction
Comprehensive Introduction to Principal Component Analysis (PCA) - Methods for Extracting Dominant Features and Reconstructing Original Signals with Code Implementation Insights
Palmprint Recognition Code: Implementation with Image Preprocessing and Feature Matching
Palmprint recognition code implementation covering image preprocessing, feature extraction, and matching algorithms with technical implementation details
Image Texture Feature Extraction Algorithm Based on Gray-Level Co-occurrence Matrix
This program implements an image texture feature extraction algorithm using Gray-Level Co-occurrence Matrix (GLCM), calculating GLCM across four distinct directions to derive texture feature vectors, followed by averaging to significantly enhance computational efficiency
Fingerprint Recognition Feature Extraction Source Code
Comprehensive fingerprint recognition feature extraction implementation, including binarization, fan-shaped region processing, and other techniques. Contains detailed Chinese explanations with multiple subroutines for clear understanding, suitable for beginners and professionals alike.
Feature Extraction of Speech Signals
Extraction of speech signal features, including methods for obtaining Mel Frequency Cepstral Coefficients (MFCC), principles of linear prediction for speech signals, and derivation of LPC features with code implementation insights
MATLAB Implementation of LBP Feature Extraction
MATLAB implementation of LBP feature extraction with getmapping.m defining three different LBP patterns and lbp.m containing the core implementation using efficient sliding-window approach for whole-image LBP transformation without regional partitioning.
Time-Frequency Domain Feature Extraction Algorithm
This algorithm performs time-frequency domain feature extraction for signals, implementing signal analysis across both time and frequency dimensions
Feature Extraction using Gabor Wavelet Filters followed by SVM Classification for Face Detection
This implementation performs feature extraction using Gabor wavelet filters, then employs Support Vector Machine (SVM) classification for face detection. The code requires MATLAB 2010 or later versions for execution, utilizing MATLAB's image processing toolbox for filter implementation and SVM functions for pattern classification.
MATLAB Algorithm for EEG Feature Extraction
MATLAB Implementation for Electroencephalogram (EEG) Feature Extraction and Signal Processing