Abstract: In order to solve the problems of low efficiency, high labor intensity and high breeding cost caused by manual operation in the identification of caged dead chickens in largescale breeding farms at present, a dead chicken identification algorithm based on temperature judgment is designed based on robot technology, infrared thermal imaging technology and image processing technology, taking laminated caged broilers as the research object. In terms of recognition algorithm, firstly, Otsu algorithm is used to segment chickens from the background, then open operation is used to remove some small noise areas, and finally the maximum temperature of the remaining area is extracted to determine whether there are dead chickens in the cage. In the aspect of hardware design, through the function analysis of the robot, the main hardware selection and system development are completed. The dead chicken detection test was carried out on the dead chicken identification robot system. The results showed that the identification rate of dead chicken in the upper coop was 83.0%, the identification rate of dead chicken in the lower coop was 77.0%, and the overall recognition rate was 80.0%.

Key words: machine vision, dead chicken recognition, caged broiler chickens, infrared thermal imaging, facilities feeding

摘要： 为解决目前规模化养殖场笼内死鸡识别主要采用人工作业方式而产生的作业效率低、劳动强度大、养殖成本高等问题，以层叠式笼养肉鸡为研究对象，基于机器人技术、红外热成像技术及图像处理等技术设计一种基于温度判断的死鸡识别算法。在识别算法方面，首先通过Otsu算法将鸡只与背景进行分割，然后利用开操作将部分小面积的噪声区域去除，最后提取剩余区域的最大温度，通过此温度确定笼内是否存在死鸡。在硬件设计方面，通过对机器人功能的分析，完成主要硬件的选型及系统开发。对死鸡识别机器人系统进行死鸡检测试验，结果表明：机器人对上层鸡笼内死鸡识别率为83.0%，对下层鸡笼内死鸡识别率为77.0%，总体识别率为80.0%。

关键词: 机器视觉, 死鸡识别, 笼养肉鸡, 红外热成像, 设施养殖