MATLAB Image Thinning and Skeleton Extraction Processing
Image Thinning: Skeleton extraction from images using MATLAB, facilitating subsequent analysis through morphological operations and feature detection algorithms
Graduate Course in Image Processing
Graduate Course in Image Processing: Fundamentals and Applications
MATLAB Implementation and Application of 2D Interpolation
Application of 2D interpolation in image processing and data visualization. Key methods include nearest-neighbor interpolation, bilinear interpolation, and cubic spline interpolation. This source code demonstrates implementation differences and algorithmic characteristics, highlighting MATLAB's interp2 function usage for grid-based interpolation scenarios.
MATLAB Code Implementation for Image Processing Sequence
Image processing sequence implementation that detects image boundaries, identifies inflection points on boundary curves, and removes duplicate coordinate points from boundary paths.
Adaptive Algorithm MATLAB Implementation for Image Processing
Utilizing adaptive algorithm MATLAB programs for image processing that overcomes the limitations of histogram equalization through dynamic contrast adjustment techniques
Image Texture Feature Extraction
Image texture feature extraction serves as another crucial low-level feature in image processing, implemented using MATLAB with code-focused explanations
Wavelet Multi-Scale Algorithm for Image Processing and Edge Detection
Image Processing and Edge Detection Using Wavelet Multi-Scale Algorithm in MATLAB
Image Processing (CAPTCHA Recognition) Program
Image Processing (CAPTCHA Recognition) Program with implementation examples and algorithm demonstrations
Image Processing GUI Developed in MATLAB
This MATLAB-based image processing GUI source code provides a comprehensive framework for various image manipulation tasks, including filtering, edge detection, and enhancement techniques.
MATLAB Code Implementation for Multi-Object Detection
Multi-object detection technique applicable to video surveillance, visual object tracking, motion detection, and other related image processing applications. Includes implementation approaches using detection algorithms and computer vision toolbox functions.