DocumentCode :
2316101
Title :
Empty bottle inspector based on machine vision
Author :
Duan, Feng ; Wang, Yao-Nan ; Liu, Huan-jun ; Tan, Wen
Author_Institution :
Coll. of Electr. & Information Eng., Hunan Univ., Changsha, China
Volume :
6
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
3845
Abstract :
A machine-vision-based empty bottle inspector is presented in this paper. The mechanical structure and electric control system are illustrated in detail. A method based on the histogram of edge points is applied for real-time determination of inspection area. For defect detection of bottle wall and bottle bottom, a derivative algorithm from Canny edge detector is proposed. In bottle finish inspection, two artificial neural networks are used for low-level inspection and high-level judgment respectively. A prototype is developed and experimental results demonstrate the feasibility of the inspector. Inspections performed by the prototype have proved the effectiveness and value of the proposed algorithms in automatic real-time inspection.
Keywords :
automatic optical inspection; brewing industry; computer vision; edge detection; neural nets; recycling; Canny edge detector; artificial neural network; bottle finish inspection; defect detection; electric control system; empty bottle inspector; machine vision; mechanical structure; Control systems; Humans; Image edge detection; Inspection; Machine vision; Particle separators; Production; Prototypes; Sensor systems; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1380507
Filename :
1380507
Link To Document :
بازگشت