Segmentation methods for a group-housed pig monitoring system
- Authors
- Ju, M.; Chung, Y.; Baek, H.; Chung, Y.; Park, D.; Park, B.
- Issue Date
- 2017
- Publisher
- Asian Research Publishing Network
- Keywords
- Group-Housed Pigs; Image Processing; Pig Management; Segmentation; Video-based Pig Monitoring
- Citation
- Journal of Theoretical and Applied Information Technology, v.95, no.17, pp.4321 - 4329
- Indexed
- SCOPUS
- Journal Title
- Journal of Theoretical and Applied Information Technology
- Volume
- 95
- Number
- 17
- Start Page
- 4321
- End Page
- 4329
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/86076
- ISSN
- 1992-8645
- Abstract
- The analysis of individual pig behavior in group-housed pigs is important for pig management. In this study, we propose two low-level segmentation methods for group-housed pigs to facilitate the video-based high-level analysis of pig behavior. In a 24-hour pig room monitoring environment where no pig is allowed to enter/leave the room during the monitored period, the previous video frame has sufficient information for separating touching-pigs in the current video frame. In this paper, we propose two methods to separate touching-pigs using the information of the previous video frame and a hybrid method for combining the segmentation results of each method. According to experimental results with the Korean pig farm data, the proposed segmentation methods based on the labeled outline/region information can provide more accurate results than widely used methods. © 2005 - Ongoing JATIT & LLS.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.