Robust pig extraction using ground base depth images for automatic weight estimation

IF 0.8 Q4 ROBOTICS
Khin Dagon Win, Kikuhito Kawasue, Tadaaki Tokunaga
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引用次数: 0

Abstract

Dark colored pigs (Berkshire, Duroc, etc.) are widely recognized nationwide in Japan for their exceptional taste, with the southern Kyushu region being a renowned production area for these esteemed breeds. However, estimating the weight of these pigs using a camera presents a unique challenge. The key process in a camera-based weight estimation system is the precise extraction of the target pig from the background. Typically, cameras capture images from above, as the top-view images provide the most specific growth indicators. However, the image from above contains a ground image. Since Berkshire and Duroc pigs are black and red, respectively, they blend into the ground, making it difficult to accurately segment the pigs in the images. Thus, it is crucial to perfectly distinguish between the ground and the pigs. Therefore, a new extraction method is proposed to distinguish between the ground and pigs by converting depth data based on the pig's position. To enhance the efficiency of pig farming and alleviate the burden on workers, our goal is to develop a system that automatically measures the weight of Berkshire pigs for shipment without background interference. In this study, we installed the system at a Berkshire pig farm and demonstrated the effectiveness of this innovative extraction method for camera-based weight estimation.

利用地基深度图像进行自动权重估计的鲁棒猪提取
深色猪(伯克郡,杜洛克等)因其独特的口味在日本全国范围内得到广泛认可,九州南部地区是这些受人尊敬的品种的著名生产区。然而,用相机估计这些猪的体重是一个独特的挑战。基于摄像机的猪重估计系统的关键是从背景中精确提取目标猪。通常,摄像机从上方拍摄图像,因为顶视图图像提供了最具体的增长指标。然而,上面的图像包含一个地面图像。由于伯克夏猪和杜洛克猪分别是黑色和红色,它们与地面混在一起,因此很难准确地在图像中分割猪。因此,完全区分地面和猪是至关重要的。为此,提出了一种基于猪的位置转换深度数据来区分地面和猪的新提取方法。为了提高养猪业的效率,减轻工人的负担,我们的目标是开发一种系统,自动测量伯克夏猪的重量,以便在没有背景干扰的情况下运输。在这项研究中,我们在伯克郡的一个养猪场安装了该系统,并证明了这种创新的提取方法在基于相机的体重估计中的有效性。
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来源期刊
CiteScore
2.00
自引率
22.20%
发文量
101
期刊介绍: Artificial Life and Robotics is an international journal publishing original technical papers and authoritative state-of-the-art reviews on the development of new technologies concerning artificial life and robotics, especially computer-based simulation and hardware for the twenty-first century. This journal covers a broad multidisciplinary field, including areas such as artificial brain research, artificial intelligence, artificial life, artificial living, artificial mind research, brain science, chaos, cognitive science, complexity, computer graphics, evolutionary computations, fuzzy control, genetic algorithms, innovative computations, intelligent control and modelling, micromachines, micro-robot world cup soccer tournament, mobile vehicles, neural networks, neurocomputers, neurocomputing technologies and applications, robotics, robus virtual engineering, and virtual reality. Hardware-oriented submissions are particularly welcome. Publishing body: International Symposium on Artificial Life and RoboticsEditor-in-Chiei: Hiroshi Tanaka Hatanaka R Apartment 101, Hatanaka 8-7A, Ooaza-Hatanaka, Oita city, Oita, Japan 870-0856 ©International Symposium on Artificial Life and Robotics
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