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.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17448)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.