Dual Tree Rotated Complex Wavelets Transform with Local Binary Patterns for Texture Image Retrieval

A. Hariprasad Reddy*, N. Subhash Chandra**
* Research Scholar, Department of Computer Science and Engineering, JNTU Hyderabad, Hyderabad, Telangana, India
** Professor & Head of the Department, VBIT, Hyderabad, Telangana, India.
Periodicity:January - March'2015
DOI : https://doi.org/10.26634/jdp.3.1.3287

Abstract

In this paper, the combination of local binary patterns (LBP) and dual tree complex wavelet filters for content based image retrieval (CBIR). A new set of two-dimensional (2-D) rotated dual tree complex wavelet transform (DT-RCWT) are designed with dual tree complex wavelet filter coefficients, which gives improved texture retrieval performance. Most texture image retrieval systems are still incapable of providing retrieval result with high retrieval accuracy and less computational complexity. To address this problem, we propose a novel approach for texture image retrieval by using a set of dual-tree rotated complex wavelet filter (DT-RCWF) dual-tree-complex wavelet transform (DT-CWT) and local binary patterns (LBP) jointly, which obtains the texture features. LBP extracts the information based on distribution of point edges which are evaluated by taking into consideration of local difference between the center pixel and its neighbors in an image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using proposed features is found to be superior to other existing methods.

Keywords

Keywords- Local Binary Patterns (LBP), Dual-Tree-Complex Wavelet Transform (DT-CWT); Dual-Tree Rotated Complex Wavelet Filter (DT-RCWF).

How to Cite this Article?

Reddy,H.A., and Chandra,S.N. (2015). Dual Tree Rotated Complex Wavelets Transform with Local Binary Patterns for Texture Image Retrieval. i-manager’s Journal on Digital Signal Processing, 3(1), 22-30. https://doi.org/10.26634/jdp.3.1.3287

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