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Content Based Image Retrieval Using Exact Legendre Moments and Support Vector Machine

Author(s): Ch.Srinivasa Rao | S.Srinivas Kumar | B.Chandra Mohan

Journal: International Journal of Multimedia & Its Applications
ISSN 0975-5934

Volume: 2;
Issue: 2;
Start page: 69;
Date: 2010;
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Keywords: CBIR | LM | ELM | Feature Extraction | Support Vector Machine.

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz.,Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are goodat representing the shape features of an image. However, non-orthogonality of MI and poorreconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal momentbased CBIR system is needed. Legendre Moments (LM) are orthogonal, computationally faster, and canrepresent image shape features compactly. CBIR system using Exact Legendre Moments (ELM) for grayscale images is proposed in this work. Superiority of the proposed CBIR system is observed over othermoment based methods, viz., MI and ZM in terms of retrieval efficiency and retrieval time. Further, theclassification efficiency is improved by employing Support Vector Machine (SVM) classifier. Improvedretrieval results are obtained over existing CBIR algorithm based on Stacked Euler Vector (SERVE)combined with Modified Moment Invariants (MMI).
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