Bilateral smoothing of gradient vector field and application to image segmentation

Hegadi, Ravindra S and Pediredla, Adithya Kumar and Seelamantula, Chandra Sekhar (2012) Bilateral smoothing of gradient vector field and application to image segmentation. In: 2012 19th IEEE International Conference on Image Processing (ICIP), Sept. 30 2012-Oct. 3 2012, Orlando, Florida, USA.

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Abstract

Medical image segmentation finds application in computer-aided diagnosis, computer-guided surgery, measuring tissue volumes, locating tumors, and pathologies. One approach to segmentation is to use active contours or snakes. Active contours start from an initialization (often manually specified) and are guided by image-dependent forces to the object boundary. Snakes may also be guided by gradient vector fields associated with an image. The first main result in this direction is that of Xu and Prince, who proposed the notion of gradient vector flow (GVF), which is computed iteratively. We propose a new formalism to compute the vector flow based on the notion of bilateral filtering of the gradient field associated with the edge map - we refer to it as the bilateral vector flow (BVF). The range kernel definition that we employ is different from the one employed in the standard Gaussian bilateral filter. The advantage of the BVF formalism is that smooth gradient vector flow fields with enhanced edge information can be computed noniteratively. The quality of image segmentation turned out to be on par with that obtained using the GVF and in some cases better than the GVF.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright of this article belongs to IEEE.
Keywords:	Bilateral Filter; Active Contour; Snake; Gradient Vector Flow (GVF); Bilateral Vector Flow (BVF)
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	02 Jul 2013 06:55
Last Modified:	02 Jul 2013 06:55
URI:	http://eprints.iisc.ac.in/id/eprint/46539

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