Hanse Ahn, Wonseok Choi, Sunhwa Park, Yongwha Chung, Daihee Park

KIPS Transactions on Software and Data Engineering, Vol. 8, No. 11, pp. 457-464, Nov. 2019
https://doi.org/10.3745/KTSDE.2019.8.11.457,   PDF Download:
Keywords: Real-Time Pig Monitoring, Posture Determining, Head Removal, image processing, Deep Learning, YOLO
Abstract

The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig’s weight is an important issue in productivity perspective. In order to estimate the pig’s weight by using the number of pig’s pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig’s posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig’s head by using light weighted image processing technique. First, we determine the pig’s posture by comparing the length from the center of the pig‘s body to the outline of the pig in the binary image. Then, we train the location of pig’s head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig’s head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig’s head. In the Experiment result, we confirmed that the pig’s posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig’s head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.

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