TY - JOUR
T1 - Automated optical inspection for abnormal-shaped packages
AU - Lin, Wei Yu
AU - Hsu, Chen Tao
AU - Chang, Chi Chun
AU - Chuang, Jen Hui
PY - 2019/1/13
Y1 - 2019/1/13
N2 - In this paper, we develop an automated optical inspection method to detect yarn packages' defect. Although textile industry is regarded as a traditional industry, many new technologies, e.g., computer vision detection algorithms, are applied to this industry in recent years. Yarn packages are the semi-finished good of textile industry. Various factors may cause abnormal-shaped packages. In this study, we develop three defect detection algorithms to extract abnormal-shape packages. These algorithms can help manufacturer to avoid the disadvantages of human inspection effectively and improve the productive quality.
AB - In this paper, we develop an automated optical inspection method to detect yarn packages' defect. Although textile industry is regarded as a traditional industry, many new technologies, e.g., computer vision detection algorithms, are applied to this industry in recent years. Yarn packages are the semi-finished good of textile industry. Various factors may cause abnormal-shaped packages. In this study, we develop three defect detection algorithms to extract abnormal-shape packages. These algorithms can help manufacturer to avoid the disadvantages of human inspection effectively and improve the productive quality.
UR - http://www.scopus.com/inward/record.url?scp=85080865725&partnerID=8YFLogxK
U2 - 10.2352/ISSN.2470-1173.2019.7.IRIACV-453
DO - 10.2352/ISSN.2470-1173.2019.7.IRIACV-453
M3 - Conference article
AN - SCOPUS:85080865725
SN - 2470-1173
VL - 2019
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
IS - 7
M1 - 453
T2 - 2019 Intelligent Robotics and Industrial Applications Using Computer Vision Conference, IRIACV 2019
Y2 - 13 January 2019 through 17 January 2019
ER -