New local sedec pattern descriptor for improving the retrieval efficiency in content-based image retrieval

S. Umamaheswaran, N. Suresh Kumar, K. Ganesh and S. Nagarajan

International Journal of Business Information Systems, 2018, vol. 27, issue 3, 349-366

Abstract: In this paper, a novel content-based image retrieval (CBIR) method is proposed using the local sedec pattern (LScP). The local binary pattern (LBP) and the local ternary pattern (LTP), encode the relationship between the referenced pixel and its surrounding pixels, by computing gray-level difference, but in a different way. The proposed methods encode the relationship between the centre pixel and its neighbours, based on directions such as vertical, horizontal and diagonal. Calculation based on first order derivatives is used here. Second order derivative is also applied to obtain LScP. The performance of the proposed method is compared with the LTrP and other local pattern (LBP, LDP and LTP) which results are obtained using benchmark image databases viz., Corel 1000 database (DB1), Brodatz texture database (DB2). Performance of the LScP shows improvement in retrieval from 75.9%/48.7% to 86.52%/54.4% in DB1, for average precision/average recall as compared with LTrP and other local patterns. A similar comparison shows improvement from 85.30% to 91.5% in terms of average retrieval rate on database DB2.

Keywords: content-based image retrieval; CBIR; local sedec patterns; LScPs; local tetra patterns; LTrPs. (search for similar items in EconPapers)
Date: 2018
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