Grain Truck Loading Status Detection Based on Machine Vision

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 数字工厂研究室

	Grain Truck Loading Status Detection Based on Machine Vision
	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
	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
内容类型	会议论文
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.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.Chinese Academy of Sciences, Shenyang Institute of Automation, 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.