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Proceedings Paper

Improved coarseness-based image retrieval
Author(s): Xinghua Sun; Jingyu Yang; Li Guo
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Paper Abstract

Coarseness is the most fundamental textural feature and has been much investigated since early studies. This paper improves the previous coarseness algorithm on the selection of neighborhood sizes and the calculation of neighborhood average differences, and the improved coarseness algorithm is presented. Experiments show that the improved coarseness has higher texture discriminability and better rotation invariance, and that the image retrieval result based on the improved coarseness is superior to that based on the previous coarseness.

Paper Details

Date Published: 26 September 2001
PDF: 5 pages
Proc. SPIE 4551, Image Compression and Encryption Technologies, (26 September 2001); doi: 10.1117/12.442893
Show Author Affiliations
Xinghua Sun, Nanjing Univ. of Science and Technology (China)
Jingyu Yang, Nanjing Univ. of Science and Technology (China)
Li Guo, Nanjing Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 4551:
Image Compression and Encryption Technologies
Jun Tian; Tieniu Tan; Liangpei Zhang, Editor(s)

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