Feature Set Reduction in Rotation Invariant CBIR Using Dual-Tree Complex Wavelet Transform

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Author(s): Deepak Sharma (Maharishi Markandeshwar University, India), Ekta Walia (Maharishi Markandeshwar University, India)and H.P. Sinha (Maharishi Markandeshwar University, India)
Copyright: 2012
Pages: 17
Source title: Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
Source Author(s)/Editor(s): Vijay Kumar Mago (Simon Fraser University, Canada)and Nitin Bhatia (DAV College, India)
DOI: 10.4018/978-1-61350-429-1.ch013

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

An accurate Content Based Image Retrieval (CBIR) system is essential for the correct retrieval of desired images from the underlying database. Rotation invariance is very important for accurate Content Based Image Retrieval (CBIR). In this chapter, rotation invariance in Content Based Image Retrieval (CBIR) system is achieved by extracting Fourier features from images on which Dual Tree Complex Wavelets Transform (DT-CWT) has been applied. Before applying DT-CWT, the Fourier feature set is reduced by exploiting the symmetry property of Fourier transform. For an N x N image, feature set has been reduced from N2/2 features to N2/4 features. This reduction in feature set increases the speed of the system. Hence, this chapter proposes a method which makes the Content Based Image Retrieval (CBIR) system faster without comprising accuracy and rotation invariance.

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Feature Set Reduction in Rotation Invariant CBIR Using Dual-Tree Complex Wavelet Transform

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