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Sign LTP and magnitude LTP for image indexing and retrieval

Sign LTP and magnitude LTP for image indexing and retrieval In this paper, a new algorithm for image indexing and retrieval is proposed by using the combinations of sign and magnitude of local ternary patterns (LTPs), which are calculated from the Local Difference Operator (LDO). The LDO separates the local region of the image into two components (the sign and the magnitude). The sign LTP operator (SLTP) is a generalised LTP operator and the magnitude LTP operator (MLTP) is calculated using the magnitude LDO (MLDO), weighted by the mean of the MLDO. The retrieval results of the proposed method are tested on three different image databases, i.e., the Corel 1000 (DB1), the Brodatz database (DB2) and the MIT VisTex database (DB3). The results after investigation show a significant improvement in terms of average retrieval precision and average retrieval rate as compared to previously reported spatial and transform domain methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Sign LTP and magnitude LTP for image indexing and retrieval

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2013.056635
Publisher site
See Article on Publisher Site

Abstract

In this paper, a new algorithm for image indexing and retrieval is proposed by using the combinations of sign and magnitude of local ternary patterns (LTPs), which are calculated from the Local Difference Operator (LDO). The LDO separates the local region of the image into two components (the sign and the magnitude). The sign LTP operator (SLTP) is a generalised LTP operator and the magnitude LTP operator (MLTP) is calculated using the magnitude LDO (MLDO), weighted by the mean of the MLDO. The retrieval results of the proposed method are tested on three different image databases, i.e., the Corel 1000 (DB1), the Brodatz database (DB2) and the MIT VisTex database (DB3). The results after investigation show a significant improvement in terms of average retrieval precision and average retrieval rate as compared to previously reported spatial and transform domain methods.

Journal

International Journal of Signal and Imaging Systems EngineeringInderscience Publishers

Published: Jan 1, 2013

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