Frequency-domain based video irregularity analysis

被引：1

作者：

Ringsleben, Frederic ^{[1
]}

Benndorf, Maik ^{[1
]}

Haenselmann, Thomas ^{[1
]}

机构：

[1] Univ Appl Sci Mittweida, Fac Appl Comp Sci & Biosci, D-09648 Mittweida, Germany

来源：

PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI) | 2017年

关键词：

Video similarity; Fourier transform; Production plant; Stroboscopic effect; Frequency domain;

D O I：

10.1109/CSCI.2017.97

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A typical task of camera systems in industrial environments is to observe cyclically recurring production patterns. This paper deals with the comparison of videos with the aim of revealing irregularities from these repeating patterns. We suggest interpreting each pixel of a video as a temporally varying signal. We show that irregularities can be detected easily in the frequency domain. Compared to existing methods, e.g. based on structure or color, we obtain a nearly lossless comparison that is able to deal with the stroboscope effect. The result is a 2D-irregularity map that shows deviations from the regular production process on a pixel-by-pixel basis.

引用

页码：572 / 575

页数：4

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