Application of Spectral Statistics to Surface Defect Detection

被引：0
|
作者：
Deborah, Hilda [1 ]
Richard, Noel [2 ]
Hardeberg, Jon Yngve [1 ]
机构：
[1] Norwegian Univ Sci & Technol, Dept Comp Sci, Trondheim, Norway
[2] Univ Poitiers, CNRS, JRU 7252, Lab XLIM, Poitiers, France
来源：
FOURTEENTH INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION | 2019年 / 11172卷
关键词：
D O I：
10.1117/12.2521714
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The development of a spectral difference-based statistical processing of hyperspectral images is provided in this article. Kullback-Leibler pseudo-divergence function, which was specifically developed for the metrological processing of hyperspectral images, is used at the foundation of the statistics. As a demonstration of its use, the proposed statistics are used in visualising surface variability within a set of pigment patches. It is then further exploited to detect anomalies and deterioration that occur on the patches.
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页数：8
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