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Proceedings Paper

True RGB line-scan camera for color machine vision applications
Author(s): Guy F. Lemstrom
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Paper Abstract

The design and technical capabilities of a true RGB 3 CCD chip color line scan camera are presented within this paper. The camera was developed for accurate color monitoring and analysis in industrial applications. A black & white line scan camera has been designed and built utilizing the same modular architecture of the color line scan camera. Color separation is made possible with a tri-chromatic RGB beam splitter. Three CCD linear arrays are precisely mounted to the output surfaces of the prism and the outputs of each CCD are exactly matched pixel by pixel. The beam splitter prism can be tailored to separate other spectral components than the standard RGB. A typical CCD can detect between 200 and 100 nm. Either two or three spectral regions can be separated using a beam splitter prism. The camera is totally digital and has a 16-bit parallel computer interface to communicate with a signal processing board. Because of the open architecture of the camera it's possible for the customer to design a board with some special functions handling the preprocessing of the data (for example RGB - HSI conversion). The camera can also be equipped with a high speed CPU-board with enough of local memory to do some image processing inside the camera before sending the data forward. The camera has been used in real industrial applications and has proven that its high resolution and high dynamic range can be used to measure minute color differences, enabling the separation or grading of objects such as minerals, food or other materials that could not otherwise be measured with a black and white camera.

Paper Details

Date Published: 10 October 1994
PDF: 9 pages
Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, (10 October 1994); doi: 10.1117/12.188921
Show Author Affiliations
Guy F. Lemstrom, TVI-Temet Vision Industry Oy (Finland)

Published in SPIE Proceedings Vol. 2353:
Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision
David P. Casasent, Editor(s)

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