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Image segmentation is a fundamental task in image analysis responsible for partitioning an image into multiple sub-regions based on a desired feature. Active contours have been widely used as attractive image segmentation methods because they always produce sub-regions with continuous boundaries, while the kernel-based edge detection methods, e.g. Sobel edge detectors, often produce discontinuous boundaries. The use of level set theory has provided more flexibility and convenience in the implementation of active contours. However, traditional edge-based active contour models have been applicable to only relatively simple images whose sub-regions are uniform without internal edges. Here in this paper we attempt to brief the taxonomy and current state of the art in Image segmentation and usage of Active Contours.
D. Baswaraj, Dr. A. Govardhan. 2012. "Active Contours and Image Segmentation: The Current State Of the Art". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F11).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
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Total Score: 153
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: D. Baswaraj, Dr. A. Govardhan, Dr. P. Premchand (PhD/Dr. count: 2)
View Count (all-time): 374
Total Views (Real + Logic): 2038
Total Downloads (simulated): 96
Publish Date: 2012 03, Thu
Monthly Totals (Real + Logic):
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