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.

引用

页数：8

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