Principal Component Analysis for Image Recognition and Feature Extraction
MATLAB-based PCA implementation for image recognition and feature extraction applications, featuring dimensionality reduction and pattern discovery capabilities.
MATLAB Image Recognition Implementation Using Matrix Computations
Image recognition system that processes geometric shapes through matrix operations, capable of distinguishing triangles, ellipses, circles, rectangles, and other regular geometric forms using MATLAB's image processing toolbox functions like regionprops and bwlabel.
MATLAB Code Implementation for Image Recognition: Techniques and Neural Network Approaches
Image recognition, text extraction, edge detection, binarization, pattern recognition design, and neural networks with MATLAB implementation examples
Source Code for Image Recognition
This source code implemented in MATLAB provides various examples of image recognition algorithms and techniques, including practical implementations of feature extraction, pattern classification, and object detection methods.
ASIFT Implementation on MATLAB with Enhanced Features
An improved ASIFT program implemented in MATLAB that delivers outstanding image recognition and matching capabilities. This enhanced version demonstrates significant performance improvements over traditional algorithms like SIFT and SURF through optimized code implementation and additional image processing features.
Common MATLAB Programs with Code Implementation Details
This collection includes dozens of practical MATLAB programs covering image denoising, image recognition, RBF neural network training, cubic spline interpolation, linear equation system solving, and more. Each program is accompanied by technical explanations of algorithms and implementation approaches.
MATLAB Object Recognition and Counting through Image Processing
MATLAB Object Recognition and Counting: Implementing object detection and quantification in images using SIMULINK programming methodology. The implementation involves image preprocessing, segmentation algorithms, and blob analysis for accurate object counting. Key files include testpart.jpg (test image), readimg.m (image reading function with imread() implementation), and imagecount.mdl (main SIMULINK model for recognition and counting). Test image features a wheel with 24 visible gaps for validation.
MATLAB Source Code Implementation of SVM Toolbox
SVM toolbox implemented in MATLAB source code, suitable for pattern recognition, image recognition, and multiple application domains with comprehensive machine learning capabilities
Image Recognition and Classification Methods
MATLAB source code for image recognition and classification methods, providing feature extraction and classification algorithm implementations using MATLAB's Image Processing Toolbox.
Standard Hough Transform Circle Detection with MATLAB Implementation
Tested MATLAB code for circle detection using standard Hough transform algorithm, suitable for computer vision and image recognition applications with detailed implementation insights