DocumentCode
2962255
Title
Identification and Location of Picking Tomatoes Based on Machine Vision
Author
Xiao-lian, Lv ; Xiao-rong, Lv ; Bing-fu, Lu
Author_Institution
Dept. of Electr. & Inf., Chuzhou Coll., Chuzhou, China
Volume
2
fYear
2011
fDate
28-29 March 2011
Firstpage
101
Lastpage
107
Abstract
Through researched the method of the identification and location based on machine vision, location information of mature tomatoes has been obtained, which can be used to guide the automated picking operation of ripe tomatoes. The segmentation of visual system is based on the difference between the color characteristics of ripe tomatoes and background. Through the gray-scale method, the treatment of the color image is turned into gray image processing, and the picking tomatoes is accurately identified using mathematical morphology, object extraction, and region filling methods. Furthermore centroid of picking tomatoes is selected as match features, and the picking tomatoes location information is determined through three-dimensional reconstruction method of space point. The experimental results show that the identification of mature fruit can reach 98%, the green ripe fruit up to 89%, positioning error can be controlled within less than 15 mm, identification and location effects can satisfactorily meet actual work requirements.
Keywords
agricultural products; computer vision; image colour analysis; image reconstruction; image segmentation; production engineering computing; color image treatment; gray image processing; gray-scale method; identification; location information; machine vision; mature fruit; object extraction; region filling methods; three-dimensional reconstruction method; tomatoes; visual system segmentation; Cameras; Equations; Image color analysis; Image segmentation; Mathematical model; Object segmentation; Pixel; centroid matching; color space; identification; location; segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location
Shenzhen, Guangdong
Print_ISBN
978-1-61284-289-9
Type
conf
DOI
10.1109/ICICTA.2011.316
Filename
5750843
Link To Document