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Open AccessArticle

Weber Texture Local Descriptor for Identification of Group-Housed Pigs

1
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
2
School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China
3
Nanjing Normal University Taizhou College, Taizhou 225300, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(16), 4649; https://doi.org/10.3390/s20164649
Received: 20 July 2020 / Revised: 12 August 2020 / Accepted: 14 August 2020 / Published: 18 August 2020
(This article belongs to the Section Sensing and Imaging)
The individual identification of group-housed pigs plays an important role in breeding process management and individual behavior analysis. Recently, livestock identification methods based on the side view or face image have strict requirements on the position and posture of livestock, which poses a challenge for the application of the monitoring scene of group-housed pigs. To address the issue above, a Weber texture local descriptor (WTLD) is proposed for the identification of group-housed pigs by extracting the local features of back hair, skin texture, spots, and so on. By calculating the differential excitation and multi-directional information of pixels, the local structure features of the main direction are fused to enhance the description ability of features. The experimental results show that the proposed WTLD achieves higher recognition rates with a lower feature dimension. This method can identify pig individuals with different positions and postures in the pig house. Without limitations on pig movement, this method can facilitate the identification of individual pigs with greater convenience and universality. View Full-Text
Keywords: Weber texture local descriptor; group-housed pigs; pig identification Weber texture local descriptor; group-housed pigs; pig identification
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Huang, W.; Zhu, W.; Ma, C.; Guo, Y. Weber Texture Local Descriptor for Identification of Group-Housed Pigs. Sensors 2020, 20, 4649.

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