TY - JOUR
T1 - Rubber hose surface defect detection system based on machine vision
AU - Meng, Fanwu
AU - Ren, Jingrui
AU - Wang, Qi
AU - Zhang, Teng
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/1/30
Y1 - 2018/1/30
N2 - As an important part of connecting engine, air filter, engine, cooling system and automobile air-conditioning system, automotive hose is widely used in automobile. Therefore, the determination of the surface quality of the hose is particularly important. This research is based on machine vision technology, using HALCON algorithm for the processing of the hose image, and identifying the surface defects of the hose. In order to improve the detection accuracy of visual system, this paper proposes a method to classify the defects to reduce misjudegment. The experimental results show that the method can detect surface defects accurately.
AB - As an important part of connecting engine, air filter, engine, cooling system and automobile air-conditioning system, automotive hose is widely used in automobile. Therefore, the determination of the surface quality of the hose is particularly important. This research is based on machine vision technology, using HALCON algorithm for the processing of the hose image, and identifying the surface defects of the hose. In order to improve the detection accuracy of visual system, this paper proposes a method to classify the defects to reduce misjudegment. The experimental results show that the method can detect surface defects accurately.
UR - http://www.scopus.com/inward/record.url?scp=85042921174&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/108/2/022057
DO - 10.1088/1755-1315/108/2/022057
M3 - Conference article
AN - SCOPUS:85042921174
SN - 1755-1307
VL - 108
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 2
M1 - 022057
T2 - 2017 3rd International Conference on Environmental Science and Material Application, ESMA 2017
Y2 - 25 November 2017 through 26 November 2017
ER -