DocumentCode :
2835026
Title :
Clump splitting via bottleneck detection
Author :
Wang, Hui ; Zhang, Hong ; Ray, Nilanjan
Author_Institution :
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
61
Lastpage :
64
Abstract :
Under-segmentation of an image with multiple objects is a common problem in image segmentation algorithms. This paper presents a novel approach for the splitting of clumps formed by multiple objects due to under-segmentation. The algorithm includes two steps: finding a pair of points for clump splitting, and joining the pair of selected points. In the first step, a pair of points for splitting is detected using a bottleneck rule, under the assumption that the desired objects have roughly convex shape. In the second step, the selected pair of splitting points is joined by finding the optimal splitting line between them, based on minimizing an image energy. The performance of this method is evaluated using images from various applications. Experimental results show that the proposed approach has several advantages over existing splitting methods in identifying points for splitting as well as finding an accurate split line.
Keywords :
image segmentation; object detection; bottleneck detection; clump splitting; image energy; image under-segmentation; Blood; Cells (biology); Conferences; Image edge detection; Image segmentation; Shape; Bottleneck; Clump Splitting; Under-segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
ISSN :
1522-4880
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2011.6116627
Filename :
6116627
Link To Document :
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