Empirical Coding for Curvature Based Linear Representation inImage Retrieval System

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 3

Abstract

Abstract : Image retrieval systems are finding their applications in all automation systems, wherein automateddecision needs to be taken based on the image contents. The prime requirement of such systems is to develop avery accurate coding system for maximum retrieval accuracy. Due to the processing error or surroundingerrors the efficiency of such systems is reduced, so for the optimization of recognition efficiency, a linear codingfor curvature based image recognition system is developed. This paper presents an approach of linearrepresentation of curvature scale coding for an image shape descriptor. In this approach, an average curvaturescale representation is done and an empirical modeling of signal decomposition is applied for featuredescription. In the process of empirical feature description, a spectral density based coding approach is alsoproposed for the selection of descriptive shape information from the extracted contour regions. This approach isnamed as Linear Curvature Empirical Coding (LCEC) which is simpler to derive shape features from curvatureinformation based on linear signal representation and coding. The results show that our proposed approachperforms better in comparison with previous known approaches.

Authors and Affiliations

Dayanand Jamkhandikar , Dr. Surendra Pal Singh , Dr. V. D. Mytri

Keywords

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  • EP ID EP105939
  • DOI -
  • Views 70
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How To Cite

Dayanand Jamkhandikar, Dr. Surendra Pal Singh, Dr. V. D. Mytri (2015).  Empirical Coding for Curvature Based Linear Representation inImage Retrieval System. IOSR Journals (IOSR Journal of Computer Engineering), 17(3), 5-16. https://europub.co.uk/articles/-A-105939