A novel multisource pig-body multifeature fusion method based on Gabor features
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A novel multisource pig-body multifeature fusion method based on Gabor features Zhen Zhong1,2,4 · Minjuan Wang1,2,3 · Wanlin Gao1,2 · Lihua Zheng1 Received: 1 March 2020 / Revised: 4 August 2020 / Accepted: 13 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The multi-source image fusion has been a hot topic during recent years because of its higher segmentation accuracy rate. However, the traditional multi-source image fusion methods could not obtain better contrast and more details of the fused image. To better detect the pig-body feature, a novel infrared and visible image fusion method for pig-body segmentation and temperature detection is proposed in non-subsampled contourlet transform (NSCT) domain, named as NSCT-GF. Firstly, the visible and infrared images were decomposed into a series of multi-scale and multi-directional sub-bands using NSCT. Then, to better represent the fine-scale of texture information, the Gabor energy map was extracted by Gabor filter with even-symmetry, and the low-frequency coefficients were fused by the maximum of Ordinal encoding. Then, to preserve the more coarse-scale and edge detail information, Gabor filter with odd-symmetry was employed to fuse high-frequency NSCT sub-bands and the fused coefficients were reconstructed into a final fusion image by inverse NSCT. Next, the pig-body shape was obtained by Ostu automatic threshold segmentation and optimized by morphological processing. Finally, the pig-body temperature was extracted based on shape segmentation. Experimental results showed that the proposed segmentation method was capable of achieving 1.84–3.89% higher average segmentation accuracy rate than the prevailing conventional methods and also improved efficiency in terms of time consumption. It lays a foundation for accurately measuring the temperature of pig-body. Keywords Pig-body segmentation · Pig-body temperature detection · Nonsubsampled contourlet transform · Gabor filter · Automatic threshold segmentation
1 Introduction Nowadays, the quality and safety of agricultural products is the most concerning issue, especially food safety related to animals. To solve the difficulty of disease control of animals and avoid the probability of human and animal cross-infection, the study on multisource feature representation method of animals has become an active research topic to segment the
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Minjuan Wang [email protected]
Extended author information available on the last page of the article
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Multidimensional Systems and Signal Processing
shape and then detect temperature of animals because of its non-contact. In this regard, the subject is selected as breeding pig-body.
1.1 Pig-body feature detection The current pig-body segmentation systems capture pig-body shape in a controlled environment as part of the body segmentation process. Under controlled illumination and background conditions, the pig-body shape segmentation method based on visible (VI) images was proposed, which achieved high accuracy (Font-I-Furnols et al. 20
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