13TSB_AgriFood Automated screening for pathologies at abattoir through computer vision based inspection of pig carcasses

13TSB_AgriFood 通过基于计算机视觉的猪尸体检查自动筛查屠宰场的病理状况

• 批准号: BB/L017385/1
• 负责人: Thomas Ploetz
• 金额: $ 22.63万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FL017385%2F1
• 关键词: 13TSB_AgriFood; Automated; screening; pathologies; abattoir

Visual inspection of carcasses is an important factor for ensuring the quality of meat products. However, manual inspection puts a strain on meat inspector resources, which effectively prevents detailed screening as, for example, for the purposes of health schemes. The aim of this project is to develop an automated system for visual screening at abattoir. The system will analyse images taken at abattoir in order to detect a number of health hazards on pig carcasses, and to screen them at slaughter for indications of underlying subclinical diseases. The project will: (1) develop a system for capturing images of carcass; (2) acquire image data sets and have experts annotate pathologies in them; (3) develop software that learns to recognise pathologies automatically; (4) validate the system on large scale datasets for the detection of routine health hazards, and disseminate results to relevant users, incl. providing feedback to farmers. The project brings together market leaders in meat production (Tulip) and supplier for abattoirs (Hellenic), pig levy board (BPEX), the UK's leading centre for research into pig science (Newcastle Univ.), and experts in computer vision and pattern recognition (Newcastle Univ. and Univ. of Dundee). It will enhance confidence in detecting health hazards in pig carcasses, aiming towards automated detection of underlying subclinical disease. Feeding this back to pig farmers will increase productivity and improve efficiency on farms through preventing further diseases. Producers will be able to make decisions about improving the health of their herd through the information they receive from the abattoir. The project will thus contribute towards sustainability and competitiveness of the UK pig Industry.

胴体的目视检查是保证肉制品质量的重要因素。然而，人工检查给肉类检查员的资源带来了压力，这实际上阻碍了详细的筛查，例如，为了健康计划的目的。该项目的目的是开发一个自动化系统，用于屠宰场的视觉筛选。该系统将分析在屠宰场拍摄的图像，以检测猪尸体上的一些健康危害，并在屠宰时筛选潜在亚临床疾病的迹象。该项目将：（1）开发一个捕获尸体图像的系统;（2）获取图像数据集，并让专家在其中注释病理;（3）开发学习自动识别病理的软件;（4）在大规模数据集上验证该系统，以检测日常健康危害，并将结果传播给相关用户，包括为农民提供反馈。该项目汇集了肉类生产（郁金香）和屠宰场供应商（希腊），猪征收委员会（BPEX），英国领先的养猪科学研究中心（纽卡斯尔大学），以及计算机视觉和模式识别专家（纽卡斯尔大学和邓迪大学）。它将增强检测猪尸体中健康危害的信心，旨在自动检测潜在的亚临床疾病。将其反馈给养猪户将通过防止进一步的疾病来提高生产力和农场效率。生产者将能够通过他们从屠宰场获得的信息做出改善牛群健康的决定。因此，该项目将有助于英国养猪业的可持续性和竞争力。

项目成果

Automated Classification for Visual-Only Postmortem Inspection of Porcine Pathology

• DOI: 10.1109/tase.2019.2960106
• 发表时间: 2020-04-01
• 期刊: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
• 影响因子: 5.6
• 作者: McKenna, Stephen;Amaral, Telmo;Kyriazakis, Ilias
• 通讯作者: Kyriazakis, Ilias

Abstract

• DOI: 10.1515/9783110602173-001
• 发表时间: 2020-04
• 期刊: Hybrid and Inorganic Perovskite Nanostructures
• 作者: Umer Zaman

Weighted atlas auto-context with application to multiple organ segmentation

• DOI: 10.1109/wacv.2016.7477605
• 发表时间: 2016-03
• 期刊: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV)
• 作者: Telmo Amaral;I. Kyriazakis;S. McKenna;T. Plötz

Multi-part segmentation for porcine offal inspection with auto-context and adaptive atlases.

• DOI: 10.1016/j.patrec.2018.07.031
• 发表时间: 2018-09-01
• 期刊: Pattern recognition letters
• 影响因子: 5.1
• 作者: McKenna S;Amaral T;Plötz T;Kyriazakis I
• 通讯作者: Kyriazakis I