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Proceedings Paper

Effect of different thresholding methods in RGB imaging
Author(s): Jari Miettinen; Heikki J. Ailisto
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Paper Abstract

Typical surface inspection tasks using RGB vision require the analysis of tens of megabytes of image data per second, with low false alarm and error escape rates. Although automatic inspection systems have become more common on production lines, for example in sawmills, there are substantial needs to improve their performance and accuracy. Detection is one very important part of image flow before defect recognition. Detection is used in order to find suspicious regions of the image, containing possibly defective areas, since defect detection has to cope with very high data rates. It has to be based on relative simple methods. In this paper we describe the effect of different thresholding methods in RGB defect detection. Threshold values were calculated for R, G and B channels, difference channels R-G, R-B and G- B and for mean values from R, G and B channels. The analysis was performed for pinewood. Error escape rate and false alarm rates were used as evaluation criteria. In this paper, R and G channel thresholding methods were the best ones.

Paper Details

Date Published: 5 October 2001
PDF: 7 pages
Proc. SPIE 4572, Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision, (5 October 2001); doi: 10.1117/12.444215
Show Author Affiliations
Jari Miettinen, VTT Electronics (Finland)
Heikki J. Ailisto, VTT Electronics (Finland)

Published in SPIE Proceedings Vol. 4572:
Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall, Editor(s)

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