Research on Iris Image Localization Algorithm Based on Active Contour Model
Investigation of iris image localization algorithm using active contour model with MATLAB implementation and code analysis
Explore MATLAB source code curated for "主动轮廓模型" with clean implementations, documentation, and examples.
Investigation of iris image localization algorithm using active contour model with MATLAB implementation and code analysis
Newly published paper "Graph Cuts-Based Active Contour Model with Selective Local or Global Segmentation" with source code included. This implementation utilizes graph cut optimization techniques for image segmentation with flexible local/global region selection capabilities. The algorithm employs energy minimization through max-flow/min-cut computations with customizable region constraints. Source code available for download!
An integrated image segmentation approach combining Graph Cut (GC) and Active Contour Model (ACM), capable of performing both local and global image segmentation with practical implementation simplicity and efficiency.
Active Contour Model, known as the snake model, is an image segmentation algorithm that leverages high-level image information for precise boundary detection and region separation.
This code and documentation implement an image segmentation approach using active contour models [snake], featuring energy minimization algorithms with internal and external energy components, along with practical implementation details for object boundary detection.
Implementation of Active Contour Model (Snake Model) with complete MATLAB source code, suitable for image segmentation, object tracking, and shape analysis tasks
Implementation of GVF (Gradient Vector Flow) and VFC (Vector Field Convolution) active contour models with MATLAB codebase, supplemented by C language programming for enhanced computational performance.
GVF Snake Algorithm Implementation and Technical Overview