
Proceedings Paper
Fuzzy-logic-based approach to color quality processingFormat | Member Price | Non-Member Price |
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Paper Abstract
The development of high resolution spectrophotometers and colorimeters, combined with its portability and large data processing abilities, has made the color evaluation process easier and faster. Although these instruments are very useful for rapid pass or fail color inspections in many industries such as, the automotive industry, textile industry, etc., the final decision depends primarily upon a subjective visual assessment. Besides spectral analysis, which is useful in colorant selection, the interrelationship between various environmental factors, metamerism, and texture and composition of the material (substrate), has made visual coordination an acceptable methodology to obtain a repeatable finish and color quality. Subjective assessment in color matching, especially in colors that closely resemble one another, leads to laborious and time consuming adjustments that have to be performed to obtain the right concentration of the colorants. Color evaluation and color mixing for a given material surface are interdependent. Although there are analytical methods that provide a means for colorant analysis, their application is cumbersome and involves complex calculations. In this paper we develop a fuzzy approach to obtain optimal color correlation between visual assessment, computed color differences, and colorant composition.
Paper Details
Date Published: 14 June 1996
PDF: 8 pages
Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); doi: 10.1117/12.243244
Published in SPIE Proceedings Vol. 2761:
Applications of Fuzzy Logic Technology III
Bruno Bosacchi; James C. Bezdek, Editor(s)
PDF: 8 pages
Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); doi: 10.1117/12.243244
Show Author Affiliations
Nadipuram R. Prasad, New Mexico State Univ. (United States)
Narasimha S. Prasad, New Mexico State Univ. (United States)
Published in SPIE Proceedings Vol. 2761:
Applications of Fuzzy Logic Technology III
Bruno Bosacchi; James C. Bezdek, Editor(s)
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