基于机器视觉的日本鲭定向装置设计与试验  

Design and experiment of a mackerel orientation device based on machine vision

作　　者：艾正茂 谭鹤群[1,2] 万鹏 AI Zhengmao;TAN Hequn;WAN Peng(College of Engineering,Huazhong Agricultural University/Ministry of Agriculture and Rural Affairs Key Laboratory of Agricultural Equipment in Mid-Lower Yangtze River,Wuhan 430070,China;Engineering Research Center of Green Development for Conventional Aquatic Biological Industry in the Yangtze River Economic Belt Ministry of Education,Wuhan 430070,China)

机构地区：[1]华中农业大学工学院/农业农村部长江中下游农业装备重点实验室,武汉430070 [2]长江经济带大宗水生生物产业绿色发展教育部工程研究中心,武汉430070

出　　处：《华中农业大学学报》2022年第2期208-216,共9页Journal of Huazhong Agricultural University

基　　金：湖北省农业科技创新中心创新团队项目(2016620000001044)。

摘　　要：针对现有鱼体定向整理装置工作环境嘈杂,工作稳定性差的问题,本研究设计了一种基于机器视觉的鱼体定向整理装置。采用卷积神经网络Resnet-18对鱼体头尾朝向进行识别,采用图像处理的方法提取鱼体轮廓并进行网格划分,通过比较灰度值大小判断鱼体的腹背朝向。当检测到鱼体尾部朝前时,气缸推杆将其推出剔除,实现鱼体头尾定向;当鱼体头部朝前时,由图像处理判断鱼体的腹背朝向,然后气缸推杆将其推送至限位板边缘,使其腹部靠边,在惯性作用下落入W型滑槽装置完成鱼体腹背定向。利用分离装置将鱼体逐条分开,并以日本鲭(Scomber japonicus)为试验对象进行样机试验。试验结果表明,鱼体定向整理成功率为93.3%,算法平均识别时间为0.038 s,平均每条鱼的定向整理时间为3.725 s,理论上鱼体定向整理的效率可达到15~16尾/min,满足鱼体定向整理的生产要求。In the process of automatically processing fish body,fish body orientation and sorting is the basis of pretreating fish body.In this article,a machine vision-based fish body orientation and sorting device was designed to solve the problems of noisy working environment and poor working stability of fish orientation and sorting devices existed.The convolutional neural network Resnet-18 was used to identify the head and tail orientation of the fish,and the image processing method was used to extract the outline of the fish body and perform grid division,then the ventral and dorsal orientation of the fish was judged by comparing the size of the grey scale value.When the tail of the fish was detected to be facing forward,the cylinder pushed it out and rejected it to achieve the head and tail orientation of the fish.When the head of the fish was facing forward,the ventral and dorsal orientation of the fish was judged by the image processing,and then the cylinder pushed it to the edge of the limit plate to bring its belly against the edge,and it fell into the W-shaped chute device under the action of inertia to complete the ventral and dorsal orientation of the fish.The results showed that the success rate of fish orientation was 93.3%.The average recognition time of the algorithm was 0.038 s,and the average orientation time of each fish was 3.725 s.Theoretically,the efficiency of fish orientation can reach 15-16 fish/min,which meets the production requirements of fish orientation.It will provide useful references for the application of fish orientation and machine vision in fishery production.

关 键 词：日本鲭 定向整理 机器视觉 深度学习 图像处理 水产品加工 

分 类 号：TS254[轻工技术与工程—水产品加工及贮藏工程] TP391.41[轻工技术与工程—食品科学与工程]