中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Grain Truck Loading Status Detection Based on Machine Vision

文献类型:会议论文

作者Liu D(刘丹)1,2,3; Wang Z(王卓)2,3; Bai XP(白晓平)2,3; Zhao YJ(赵泳嘉)2,3
出版日期2019
会议日期July 5-7, 2019
会议地点Xiamen, China
关键词ant lion cellular neural network edge detection grain identificationg
页码40-44
英文摘要In order to improve the efficiency of the combined harvester-grain truck operation, and realize the non-stop unloading of grain, a machine vision-based method for detecting the loading status of the grain truck is introduced. We propose a edge detection model of the cellular neural network (CNN) using the ant lion optimization algorithm (ALO) to identify the edge of the grain bin, and segment the grain bin area by improved random line detection (RLD) method. The grain area is obtained by HSV color feature transformation and the grain convex hull is obtained by the convex hull algorithm. The distance from the grain hull to the edge of the grain bin is measured in real time, and a threshold is preset to determine the loading status of each part of the grain bin.
源文献作者College of Computer Science and Technology, Huaqiao University ; Digital Communications and Networks, Chongqing University of Posts and Telecommunications ; IEEE
产权排序1
会议录2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019
会议录出版者IEEE
会议录出版地New York
语种英语
ISBN号978-1-7281-2325-7
源URL[http://ir.sia.cn/handle/173321/26842]  
专题沈阳自动化研究所_数字工厂研究室
通讯作者Liu D(刘丹)
作者单位1.University of Chinese Academy of Sciences, Beijing 100046, China
2.Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang 110016, China
3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
推荐引用方式
GB/T 7714
Liu D,Wang Z,Bai XP,et al. Grain Truck Loading Status Detection Based on Machine Vision[C]. 见:. Xiamen, China. July 5-7, 2019.

入库方式: OAI收割

来源:沈阳自动化研究所

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