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http://dx.doi.org/10.3837/tiis.2021.09.006

Multi-scale Local Difference Directional Number Pattern for Group-housed Pigs Recognition  

Huang, Weijia (School of Electrical and Information Engineering, Jiangsu University)
Zhu, Weixing (School of Electrical and Information Engineering, Jiangsu University)
Zhang, Zhengyan (School of Electronics and Information, Jiangsu University of Science and Technology)
Guo, Yizheng (Nanjing Normal University Taizhou College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.9, 2021 , pp. 3186-3203 More about this Journal
Abstract
In this paper, a multi-scale local difference directional number (MLDDN) pattern is proposed for pig identification. Firstly, the color images of individual pig are converted into grey images by the most significant bits (MSB) quantization, which makes the grey values have better discrimination. Then, Gabor amplitude and phase responses on different scales are obtained by convoluting the grey images with Gabor masks. Next, by calculating the main difference of local edge directions instead of traditionally edge information, the directional numbers of Gabor amplitude and phase responses are encoded. Finally, the block histograms of the encoded images are concatenated on each scale, and the maximum pooling is adopted on different scales to avoid the high feature dimension. Experimental results on two pigsties show that MLDDN impressively outperforms the other widely used local descriptors.
Keywords
Multi-scale local difference directional number; Gabor filter; Pig identification;
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