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An object recognition method using the improved snake algorithm

Authors
Zhang, Q.Eun, S.-J.Kim, H.Whangbo, T.-K.
Issue Date
2012
Keywords
Curve fitting; Greedy snake algorithm; Image processing; Object recognition; Snake point
Citation
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
Journal Title
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17448
DOI
10.1145/2184751.2184864
ISSN
0000-0000
Abstract
The general object recognition method is based on the area segmentation algorithm. Among the many area segmentation methods, the representative Active Contour Model (ACM), the snake model, was used in this paper for effective object recognition. The proposed method involved snake point allotment, contour line convergence, and improvement of the corrected portions, and the method recognized objects stably as a result of medical imaging. This study was conducted to minimize the post-processing cost of area segmentation. Future studies will be conducted to develop an algorithm for more efficient and accurate object recognition by complementing corrective work with contour line convergence work. © 2012 ACM.
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Whangbo, Taeg Keun
College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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