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<p>Fabric defect detection algorithm based on PHOG and SVM</p>

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Title Statement <p>Fabric defect detection algorithm based on PHOG and SVM</p>
 
Added Entry - Uncontrolled Name Cuifang, Zhao ; zhejiang normal University
Yu, Chen
Jiacheng, Ma
zhejiang normal University
 
Uncontrolled Index Term Defect detection;Fabric image;Pyramid histogramof edge orientation gradients;Support vectormachin
 
Summary, etc. <p style="text-align: justify;">In order to effectively improve the detection probabilityfor different types of fabrics and defects, a fabric defectdetection method based on pyramid histogram of edge orientationgradients (PHOG) and support vector machine (SVM) has beenproposed. The algorithm combines fabric texture statisticalmethod and machine learning method. It has two main parts,namely the feature extraction and classification. The detectionprocess mainly includes image segmentation, PHOG featureextraction, SVM model training and detection classification. Thesimulation results show that, based on the detection rate and thefalse alarm rate, the algorithm has a good detection andclassification effect, has a certain robustness, and can be appliedto the actual production department.</p>
 
Publication, Distribution, Etc. Indian Journal of Fibre & Textile Research (IJFTR)
2020-03-11 16:58:31
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/IJFTR/article/view/22046
 
Data Source Entry Indian Journal of Fibre & Textile Research (IJFTR); ##issue.vol## 45, ##issue.no## 1 (2020): INDIAN JOURNAL OF FIBRE & TEXTILE RESEARCH
 
Language Note en
 
Nonspecific Relationship Entry http://op.niscair.res.in/index.php/IJFTR/article/download/22046/465468913
http://op.niscair.res.in/index.php/IJFTR/article/download/22046/465469021
http://op.niscair.res.in/index.php/IJFTR/article/download/22046/465469022