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Proceedings Paper

Vision-based reading system for color-coded bar codes
Author(s): Erhard Schubert; Axel Schroeder
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Paper Abstract

Barcode systems are used to mark commodities, articles and products with price and article numbers. The advantage of the barcode systems is the safe and rapid availability of the information about the product. The size of the barcode depends on the used barcode system and the resolution of the barcode scanner. Nevertheless, there is a strong correlation between the information content and the length of the barcode. To increase the information content, new 2D-barcode systems like CodaBlock or PDF-417 are introduced. In this paper we present a different way to increase the information content of a barcode and we would like to introduce the color coded barcode. The new color coded barcode is created by offset printing of the three colored barcodes, each barcode with different information. Therefore, three times more information content can be accommodated in the area of a black printed barcode. This kind of color coding is usable in case of the standard 1D- and 2D-barcodes. We developed two reading devices for the color coded barcodes. First, there is a vision based system, consisting of a standard color camera and a PC-based color frame grabber. Omnidirectional barcode decoding is possible with this reading device. Second, a bi-directional handscanner was developed. Both systems use a color separation process to separate the color image of the barcodes into three independent grayscale images. In the case of the handscanner the image consists of one line only. After the color separation the three grayscale barcodes can be decoded with standard image processing methods. In principle, the color coded barcode can be used everywhere instead of the standard barcode. Typical applications with the color coded barcodes are found in the medicine technique, stock running and identification of electronic modules.

Paper Details

Date Published: 21 February 1996
PDF: 10 pages
Proc. SPIE 2665, Machine Vision Applications in Industrial Inspection IV, (21 February 1996); doi: 10.1117/12.232252
Show Author Affiliations
Erhard Schubert, Univ. Siegen (Germany)
Axel Schroeder, Univ. Siegen (Germany)


Published in SPIE Proceedings Vol. 2665:
Machine Vision Applications in Industrial Inspection IV
A. Ravishankar Rao; Ning Chang, Editor(s)

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