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An Efficient Similarity Measure for Color-Based Image Retrieval

Israa Khidher et al · University of Mosul, College of Education for Pure Science · 2008

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Author / responsible party
Israa Khidher et al
Publisher
University of Mosul, College of Education for Pure Science
Year
2008
ISSN
1812-125X
ISSN
1812-125X
Language
English
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Abstract<br /> Similarity measures are an important factor in the Content-Based Image Retrieval (CBIR). This paper finds the most efficient similarity measure from four image similarity measures. Related work on (CBIR) indicated that these measures have significantly improved the retrieval performance. These measures are the Chi-Squared, The Weighted Mean Variance distance (WMV), The Euclidean distance, and Cosine distance. A sample of 50 colored images is selected from CALTECH visual database. These images were transformed to (HSV) color space. Color features were extracted; these features are the color moments. Experimental results of the proposed work show that the Euclidean distance measure is the most efficient measure for color based image retrieval.

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APA 7

al, I. K. E. (2008). An Efficient Similarity Measure for Color-Based Image Retrieval. https://doi.org/10.33899/edusj.2008.51283

MLA

al, Israa Khidher et. "An Efficient Similarity Measure for Color-Based Image Retrieval." 2008. https://doi.org/10.33899/edusj.2008.51283.

Chicago

al, Israa Khidher et. 2008. "An Efficient Similarity Measure for Color-Based Image Retrieval.". https://doi.org/10.33899/edusj.2008.51283.

Harvard

al, I. K. E. 2008, An Efficient Similarity Measure for Color-Based Image Retrieval, University of Mosul, College of Education for Pure Science, available at: https://doi.org/10.33899/edusj.2008.51283 [Accessed 6 Aug. 2026].

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Title
An Efficient Similarity Measure for Color-Based Image Retrieval
Author / contributors
Israa Khidher et al
Publisher
University of Mosul, College of Education for Pure Science
Publication year
2008
ISSN
1812-125X
ISSN
1812-125X
Language
English

Subjects

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similarity measure; color-based image; image retrieval
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