Total variation flow-based multiscale framework for unsupervised surface defect segmentation

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Finding defects with automatic visual inspection techniques is an essential task in various industrial fields. Despite considerable studies to achieve this task successfully, most previous methods are still vulnerable to ambiguities from diverse shapes and sizes of defects. We introduce a simple yet powerful method to segment defects on various texture surfaces in an unsupervised manner. Specifically, our method is based on the multiscale scheme of the phase spectrum of Fourier transform. The proposed method can even handle one-dimensional long defect patterns (e. g., streaks by scratch), which have been known to be hard to process in previous methods. In contrast to traditional inspection methods limited to locating particular sorts of defects, our approach has the advantage that it can be applied to segmenting arbitrary defects, because of the nonlinear diffusion involved in the multiscale scheme. Extensive experiments demonstrate that the proposed method provides much better results for defect segmentation than several competitive methods presented in the literature. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.12.127201]
Publisher
SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Issue Date
2012-12
Language
English
Article Type
Article
Keywords

INSPECTION; DIFFUSION; IMAGE; SPACE; MODEL

Citation

OPTICAL ENGINEERING, v.51, no.12

ISSN
0091-3286
DOI
10.1117/1.OE.51.12.127201
URI
http://hdl.handle.net/10203/173862
Appears in Collection
EE-Journal Papers(저널논문)
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