Feature Extraction of Fruit Images
This graduation project implements practical fruit image feature extraction by simply running the "apple.m" MATLAB script, which serves as the main executable file for the image processing pipeline.
Feature Extraction for Signals and Images
Nonnegative Matrix Factorization (NMF) – A Technique for Feature Extraction in Signals and Images, Also Applicable for Image Compression
Extraction of 16 Time Domain and Frequency Domain Signal Features: Mean, Standard Deviation, Variance, and Key Statistical Indicators
Comprehensive Signal Feature Extraction Using 16 Statistical Metrics: Mean, Standard Deviation, Variance, Skewness, Kurtosis, Peak-to-Peak, Peak Value, RMS Amplitude, Average Amplitude, Root Amplitude, Waveform Factor, and Crest Factor with Code Implementation Insights
Image Stitching Implementation using MATLAB
This program implements image feature extraction using the SIFT algorithm, followed by initial feature matching, outlier removal via Random Sample Consensus (RANSAC), and final image fusion to create seamless panoramic images.
ECG Signal QRS Complex Feature Extraction Using Differential Threshold Method
MATLAB implementation for ECG signal QRS complex feature extraction utilizing differential threshold method
Face Detection, Feature Extraction, and Facial Recognition
Yale Database, PCA, SVM, MATLAB Implementation - Comprehensive Guide to Face Detection, Feature Extraction, and Recognition Algorithms
Feature Extraction in Pattern Recognition or Preprocessing in Pattern Classification
Preprocessing for feature ordering before feature extraction, performing feature ranking on m*n column data, with implementations including correlation analysis, variance thresholding, and mutual information scoring algorithms for optimal feature selection in pattern recognition and classification systems.
A Novel Algorithm for Feature Extraction Implementation
Analytical Processing Techniques for Enhanced Feature Extraction
Feature Extraction Using Gabor Wavelets for Biometric Recognition
A comprehensive MATLAB implementation for image processing using Gabor wavelet feature extraction followed by Support Vector Machine (SVM) classification, applicable to palmprint, face, and fingerprint recognition systems with detailed code implementation strategies.
PCA-Based Feature Extraction Source Code
Source code for PCA-based feature extraction implemented in MATLAB language (PCA refers to Principal Component Analysis)