SASI: a generic texture descriptor for image retrieval

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2003-11-01

Author

Carkacioglu, A
Yarman-Vural, F

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In this paper, a generic texture descriptor, namely, Statistical Analysis of Structural Information (SASI) is introduced as a representation of texture. SASI is based on statistics of clique autocorrelation coefficients, calculated over structuring windows. SASI defines a set of clique windows to extract and measure various structural properties of texture by using a spatial multi-resolution method. Experimental results, performed on various image databases, indicate that SASI is more successful then the Gabor Filter descriptors in capturing small granularities and discontinuities such as sharp corners and abrupt changes. Due to the flexibility in designing the clique windows, SASI reaches higher average retrieval rates compared to Gabor Filter descriptors. However, the price of this performance is increased computational complexity. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Subject Keywords

Signal Processing, Software, Artificial Intelligence, Computer Vision and Pattern Recognition

URI

https://hdl.handle.net/11511/65631

Journal

PATTERN RECOGNITION

DOI

https://doi.org/10.1016/s0031-3203(03)00171-7

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Department of Computer Engineering, Article

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Citation Formats

A. Carkacioglu and F. Yarman-Vural, “SASI: a generic texture descriptor for image retrieval,” PATTERN RECOGNITION, pp. 2615–2633, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65631.