Gradient vector flow: Difference between revisions

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Revision as of 03:38, 30 March 2020

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'''Gradient vector flow''' ('''GVF'''), a [[computer vision]] framework introduced by [http://iacl.ece.jhu.edu/~chenyang/ Chenyang Xu] and [http://www.iacl.ece.jhu.edu/index.php/Prince Jerry L. Prince]

<ref name=":1"> C. Xu and J.L. Prince, "Gradient Vector Flow: A New External Force for Snakes," Proc. IEEE Conf. on Comp. Vis. Patt. Recog. (CVPR), Los Alamitos: Comp. Soc. Press, pp. 66–71, June 1997, http://iacl.ece.jhu.edu/pubs/p087c.pdf</ref>

<ref name=":2">{{Cite journal | title = Snakes, Shapes, and Gradient Vector Flow| journal = IEEE Transactions on Image Processing | volume = 7| issue = 3| pages = 359-369| year = 1998| last1 = Xu | first1 = C.| last2 = Prince | first2 = J. L. | url = http://iacl.ece.jhu.edu/pubs/p084j.pdf}}</ref>, is the vector field that is produced by a process that smooths and diffuses an input vector field, and is usually used to create a vector field that points to object edges from a distance. It's widely used in object tracking, shape recognition, [[Image segmentation|segmentation]], and [[edge detection]]. In particular, it's commonly used in conjunction with [[active contour model]].

[[File:Gradient Vector Flow 3D Metasphere Example Result.png|thumb|Results from Gradient Vector Flow algorithm applied to 3-D Metasphere data]]