Keywords
image segmentation, tobogganing, edge model parameters
Abstract
Intelligent Scissors is an interactive image segmentation tool that allows a user to select piece-wise globally optimal contour segments that correspond to a desired object boundary. We present a new and faster method of computing the optimal path by over-segmenting the image using tobogganing and then imposing a weighted planar graph on top of the resulting region boundaries. The resulting region-based graph is many times smaller than the previous pixel-based graph, thus providing faster graph searches and immediate user interaction. Further, tobogganing provides an new systematic and predictable framework for computing edge model parameters, allowing subpixel localization as well as a measure of edge blur.
Original Publication Citation
Eric Mortensen and William Barrett. "Toboggan-Based Intelligent Scissors with a Four-Parameter Edge Model," IEEE/CVPR99 Proceedings, pp. 452-458, June, 1999.
BYU ScholarsArchive Citation
Barrett, William A. and Mortensen, Eric N., "Toboggan-Based Intelligent Scissors with a Four-Parameter Edge Model" (1999). Faculty Publications. 616.
https://scholarsarchive.byu.edu/facpub/616
Document Type
Peer-Reviewed Article
Publication Date
1999-06-01
Permanent URL
http://hdl.lib.byu.edu/1877/2625
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
© 1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
http://lib.byu.edu/about/copyright/