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Rotation invariant textural feature extraction for image retrieval using eigen value analysis of intensity gradients and multi-resolution analysis
Authors:Rahul Das Gupta  Jatindra K. Dash
Affiliation:1. Centre for Educational Technology, Signal Processing Group, Indian Institute of Technology, Kharagpur 721302, India;2. Department of Electronics & Electrical Communication Engineering, Indian Institute of Technology, Kharagpur 721302, India
Abstract:In this paper a novel rotation invariant multi-resolution based texture retrieval technique is proposed. The rotation invariance is achieved by aligning the direction of maximum variation of intensity gradient (defined as principal texture direction) along the reference axis. The principal direction is determined using eigen value analysis of gradient image. Wavelet transform based techniques are applied on the rotated image. The independent representation of textural energies along various directions enhances the retrieval performance over the existing rotation invariant wavelet based techniques which achieve rotation invariance by averaging the direction sensitive components. Extensive experiments on Brodatz database support this postulate.
Keywords:Content based image retrieval (CBIR)  Principal texture direction  Discrete Wavelet Transform (DWT)  Rotated Wavelet Filter (RWF)  Dual Tree Complex Wavelet Transform (DT-CWT)  Dual Tree Rotated Complex Wavelet Filter (DT-RCWF)
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