Optimization of Weighted Curvature for Image Segmentation

Details Optimization of Weighted Curvature for Image Segmentation Optimization of Weighted Curvature for Image Segmentation

2010-06-21

arxiv.org/abs/1006.4175v1

Computer Science

Computer Vision and Pattern Recognition

15 pages , 6 figures

Scientific paper

Minimization of boundary curvature is a classic regularization technique for image segmentation in the presence of noisy image data. Techniques for minimizing curvature have historically been derived from descent methods which could be trapped in a local minimum and therefore required a good initialization. Recently, combinatorial optimization techniques have been applied to the optimization of curvature which provide a solution that achieves nearly a global optimum. However, when applied to image segmentation these methods required a meaningful data term. Unfortunately, for many images, particularly medical images, it is difficult to find a meaningful data term. Therefore, we propose to remove the data term completely and instead weight the curvature locally, while still achieving a global optimum.

Affiliated with

Also associated with

No associations

Rating

Optimization of Weighted Curvature for Image Segmentation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Optimization of Weighted Curvature for Image Segmentation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimization of Weighted Curvature for Image Segmentation will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-107272