Title :
A framework for multiple snakes
Author :
Srinark, Thitiwan ; Kambhamettu, Chandra
Author_Institution :
Dept. of Comput. & Inf. Sci., Delaware Univ., Newark, DE, USA
Abstract :
A framework for segmenting multiple objects in an image based on deformable contours is proposed. In this framework, multiple snakes are applied with a new kind of energy called the "group energy." The group energy is introduced to handle sharing of properties across multiple objects in the image. Our framework allows contours of "strong objects" to guide contours of "weak objects" by utilizing deformable templates. We also automatically generate the necessary weighting parameters for energy minimization. A new approach for multiple snake optimization which is based on dynamic programming is also proposed. We applied our framework to the problem of image analysis of gene expression in microarrays. Comprehensive experiments were performed and comparisons were made between the individual energy based method and the proposed group energy based method. Our results are highly encouraging and have many potential applications in a variety of tracking scenarios.
Keywords :
biology computing; dynamic programming; edge detection; genetics; image segmentation; tracking; deformable contours; deformable templates; dynamic programming; energy minimization; gene expression; group energy; group energy based method; image; image analysis; individual energy based method; microarrays; multiple object segmentation; multiple snake optimization; multiple snakes; strong objects; tracking; weak objects; weighting parameters; Active contours; Contracts; Data mining; Deformable models; Dynamic programming; Image edge detection; Image quality; Image segmentation; Image sequence analysis; Object detection;
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1272-0
DOI :
10.1109/CVPR.2001.990960