Abstract
Active contour models, otherwise known as snakes, are extensively used in image processing and computer vision applications. However, although the approach is popular for detecting the contours of smooth convex objects, it is much more problematic in handling images containing an object with concave parts or sharp corners, or multiple objects. We further develop our segmented snake approach to contour detection and illustrate its flexibility by showing how it can be adapted to yield a dividing snake algorithm for use in multiple object segmentation. We also introduce a snake relaxation technique that can improve the convergence of the snake contour onto the object boundary.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
