NDLI: A classification method of glass defect based on multiresolution and information fusion

Content Provider	Springer Nature Link
Author	Liu, Huai guang Chen, You ping Peng, Xiang qian Xie, Jing ming
Copyright Year	2011
Abstract	The existence of defects is a key factor for quality degradation of float glass. This paper introduces an approach of glass defect identification based on multiresolution and information fusion analysis. With the help of 2D discrete wavelet transform, the subtracting defect image with a valid region is decomposed into approximated subimages and detailed subimages. The approximated subimages in three-level scales and the original defect image are chosen to proceed recognition with artificial neural network and fuzzy k-nearest neighbor. The decisive vectors from four classifiers are fused by an improved Dempster–Shafer (DS) evidence theory with head difference calibration-DS. Besides, a twice OTSU segmentation method as well as ten statistic features are interpreted for the preparation of defect recognition. The results of application indicate that the proposed algorithm can significantly increase the correct recognition rate of glass defects in five classes.
Starting Page	1079
Ending Page	1090
Page Count	12
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	56
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-04-05
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multiresolution analysis Information fusion Discrete wavelet transform Dempster–Shafer Defect recognition Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design Industrial and Production Engineering Production/Logistics/Supply Chain
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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