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Proceedings Paper

Color characterization for image indexing and machine vision
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Paper Abstract

Color representation and comparison based on the histogram has proved to be very efficient for image indexing in content-based image retrieval and machine vision applications. However, the issues of color constancy and accurate color similarity measures remain unsolved. This paper presents a new algorithm for intensity- insensitive color characterization for image retrieval and machine vision applications. The color characterization algorithm divides the HSI (hue, saturation and intensity) color space into a given number of bins in such a way that the color characterization represents all the colors in the hue/saturation plane as well as black, white and gray colors. The color distribution in these bins of the HSI space is represented in the form of a one-dimensional vector called Color Spectrum Vector (CSV). The color information that is stored in the CSV is insensitive to changes in the luminance. A weighted version of CSV called WCSV is introduced to take the similarity of the neighboring bins into account. A Fuzzy Color Spectrum Vector (FCSV) color representation vector that takes into account the human uncertainty in color classification process is also introduced here. The accuracy and speed of the algorithm is demonstrated in this paper through a series of experiments on image indexing and machine vision applications.

Paper Details

Date Published: 13 November 2000
PDF: 11 pages
Proc. SPIE 4116, Advanced Signal Processing Algorithms, Architectures, and Implementations X, (13 November 2000); doi: 10.1117/12.406523
Show Author Affiliations
Siming H. Lin, National Instruments Corp. (United States)
Dinesh Nair, National Instruments Corp. (United States)


Published in SPIE Proceedings Vol. 4116:
Advanced Signal Processing Algorithms, Architectures, and Implementations X
Franklin T. Luk, Editor(s)

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