Computer Vision Demonstration WebsiteElectronics and Computer Science |
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Active Contours & SnakesThe Greedy Snake algorithm is a feature extraction technique, also known as active contours. It works like stretched Elastic Band being released. The Initial Points are defined around feature to be extracted. The points then move through an iterative process to move to a point with the lowest energy function. in the applet below, the user can draw an elipse on the image. The animate button starts the iterative process.
How it worksThe explicitly defined ellipse creates a pre-defined number of points (based on the snake spacing). These points move to the lowest energy point in the Local Neighbourhood, defined by the "Energy Function". This continues until the snakes stop moving. There are three components to the Energy Function:
Each Weighted by Specified Parameter: Total Energy = α · Continuity + β · Curvature + γ · Image Choose different values dependent on Feature to extract:
CodeImage processing classes: Demo framework: The pages were designed and developed for educational purposes only, to demonstrate how computer vision techniques work. They are designed for no other purpose and neither the authors nor their institutions accept any liability concerning use of these pages. LinksMark Nixon & Alberto Aguado, 2002, Feature Extraction & Image Processing, Newnes http://www.markschulze.net/snakes/ - Snake Applet & Explanation of Algorithm http://torina.fe.uni-lj.si/~tomo/ac/Snakes.html - Another Snake Applet http://web.mit.edu/stanrost/www/cs585p3/p3.html – Explanation + Matlab Implementation http://homepages.inf.ed.ac.uk/cgi/rbf/CVONLINE/entries.pl?TAG709 – Repository of Greedy Snake Links
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ECS | Feature Extraction & Image Processing | © 2005 University of Southampton |