ICIC 2014: Intelligent Computing Methodologies pp 265-270 | Cite as
Shape and Color Based Segmentation Using Level Set Framework
Abstract
We propose a level set based variational approach that incorporates shape and color prior into Local Chan-Vese model for segmentation problem. Object detection and segmentation can be facilitated by the availability of a reference object. In our model, besides the level set function for segmentation, we introduce another labelling level set function to indicate the regions on which the prior shape and color should be compared. The active contour is able to find boundaries that are similar in shape and color to the prior, even when the entire boundary is not visible in the image. The experimental results demonstrate that the proposed model can efficiently segment the objects.
Keywords
Level Set Framework shape prior color prior segmentationPreview
Unable to display preview. Download preview PDF.
References
- 1.Chan, T.F.: Vese: Active contours without edges. IEEE Transaction on Image Processing, 266–277 (2001)Google Scholar
- 2.Chen, F., Yu, H., Hu, R.: Shape sparse representation for joint object classification and segmentation. IEEE Transaction on Image Processing, 992–1004 (2013)Google Scholar
- 3.Andersson, T., Lathen, G., Lenz, R.: Modified gradient search for level set based image segmentation. IEEE Transaction on Image Processing, 621–630 (2013)Google Scholar
- 4.Zhang, K., Zhang, L.: Active contours with selective local or global segmentation: A new formulation and level set method. Image and Vision Computing, 668–676 (2010)Google Scholar
- 5.Leventon, M., Faugeraus, O., Grimson, W.: Level set based segmentation with intensity and curvature priors. Mathematical Methods in Biomedical Image Analysis (2000)Google Scholar
- 6.Wang, X.F., Huang, D.S., Xu, H.: An efficient local Chan-Vese model for image segmentation. Pattern Recognition, 603–618 (2010)Google Scholar
- 7.Cremers, D., Sochen, N., Schnorr, C.: Towards recognition-based variational segmentation using shape priors and dynamic labeling. In: Griffin, L.D., Lillholm, M. (eds.) Scale-Space 2003. LNCS, vol. 2695, pp. 388–400. Springer, Heidelberg (2003)CrossRefGoogle Scholar
- 8.Riklin-Raviv, T., Kiryati, N., Sochen, N.: Prior-Based Segmentation by Projective Registration and Level Sets. In: Int’l Conf. Computer Vision, pp. 204–211 (2005)Google Scholar