An object recognition method using the improved snake algorithm

Qian Zhang, Sung Jong Eun, Hyeonjin Kim, Taeg Keun Whangbo

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
DOIs
StatePublished - 8 May 2012
Event6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12 - Kuala Lumpur, Malaysia
Duration: 20 Feb 201222 Feb 2012

Publication series

NameProceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12

Other

Other6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
CountryMalaysia
CityKuala Lumpur
Period20/02/1222/02/12

Fingerprint

Object recognition
Medical imaging
Processing
Costs

Keywords

  • Curve fitting
  • Greedy snake algorithm
  • Image processing
  • Object recognition
  • Snake point

Cite this

Zhang, Q., Eun, S. J., Kim, H., & Whangbo, T. K. (2012). An object recognition method using the improved snake algorithm. In Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12 [97] (Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12). https://doi.org/10.1145/2184751.2184864
Zhang, Qian ; Eun, Sung Jong ; Kim, Hyeonjin ; Whangbo, Taeg Keun. / An object recognition method using the improved snake algorithm. Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12. 2012. (Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12).
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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.",
keywords = "Curve fitting, Greedy snake algorithm, Image processing, Object recognition, Snake point",
author = "Qian Zhang and Eun, {Sung Jong} and Hyeonjin Kim and Whangbo, {Taeg Keun}",
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Zhang, Q, Eun, SJ, Kim, H & Whangbo, TK 2012, An object recognition method using the improved snake algorithm. in Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12., 97, Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12, 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12, Kuala Lumpur, Malaysia, 20/02/12. https://doi.org/10.1145/2184751.2184864

An object recognition method using the improved snake algorithm. / Zhang, Qian; Eun, Sung Jong; Kim, Hyeonjin; Whangbo, Taeg Keun.

Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12. 2012. 97 (Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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AB - 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.

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Zhang Q, Eun SJ, Kim H, Whangbo TK. An object recognition method using the improved snake algorithm. In Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12. 2012. 97. (Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12). https://doi.org/10.1145/2184751.2184864