Abstract
Searching for similar images is an important research topic for multimedia database management. This paper uses a quality index model to search for similar images from digital image databases. In order to speed up retrieval, the quality index model is partitioned into three factors: loss of correlation, luminance distortion, and contrast distortion. The method is performed on three different image databases to test for retrieval accuracy and category retrieval ability. The experimental results show that the proposed method performs better than the color histogram method, the color moment method, and the CDESSO method.
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Chang, CC., Lu, TC. (2005). Method for Searching Similar Images Using Quality Index Measurement. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_169
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DOI: https://doi.org/10.1007/11552451_169
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28895-4
Online ISBN: 978-3-540-31986-3
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