NDLI: A Region-Based Active Contour Model for Image Segmentation

Content Provider	IEEE Xplore Digital Library
Author	Tian Yun Zhou Ming-quan Wu Zhong-ke Wang Xing-ce
Copyright Year	2009
Abstract	The task of image segmentation is to partition an image into non-overlapping regions based on intensity or textural information. The active contour methods provide an effective way for segmentation, in which the boundaries of the objects are detected by evolving curves. In this paper, we propose a new region-based active contour model, which is based on the image global information for the stopping process. As a result, the model is robust to noise. Level set representation is used for the moving curves so that the topological changes during the evolution are handled automatically. Furthermore, an internal energy term is introduced, and it forces the level set function to be close to a signed distance function, which avoids the costly re-initialization for the evolving level set function. Experimental results demonstrate desirable performance of our model for images with large noise and complicated structures. Comparisons with Chan-Vese model and RSF model show the advantages of the model in terms of efficiency and accuracy.
Starting Page	376
Ending Page	380
File Size	884411
Page Count	5
File Format	PDF
ISBN	9781424454112
e-ISBN	9781424454129
DOI	10.1109/CIS.2009.238
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Minimization methods Level set re-initialization Educational institutions global intensity fitting energy Electronic mail Active contours Image segmentation Information science Information security Object detection noise active contour internal energy Computational intelligence
Content Type	Text
Resource Type	Article

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