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      Trademark Image Retrieval Using Multiple Features

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      Challenge of Image Retrieval (CIR)

      Image Retrieval

      25th - 26th February 1999

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          Abstract

          This paper describes an ongoing research project aimed at implementing a trademark retrieval system using an associative memory neural network. The novel aspect presented in this paper is the proposed integrated framework for image retrieval using multiple representations of images based on gestalt principles. In this paper we summarise the methods we followed in extracting local perceptual features as well as features of the closed figures of images. In designing the search engine of the system we have adopted a novel similarity assessment criteria based on local features as well as features of the closed figures, which is being implemented using an associative memory neural network to achieve high performance in retrieval. Then we describe the strategy we followed in combining multiple similarity measures and present the results obtained from the first phase of evaluation of the system.

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          Author and article information

          Contributors
          Conference
          February 1999
          February 1999
          : 1-11
          Affiliations
          Department of Computer Science

          University of York

          York, Y010 5DD, UK
          Article
          10.14236/ewic/CIR1999.10
          © Sujeewa Alwis et al. Published by BCS Learning and Development Ltd. Challenge of Image Retrieval

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Challenge of Image Retrieval
          CIR
          Newcastle upon Tyne, UK
          25th - 26th February 1999
          Electronic Workshops in Computing (eWiC)
          Image Retrieval
          Product
          Product Information: 1477-9358BCS Learning & Development
          Self URI (journal page): https://ewic.bcs.org/
          Categories
          Electronic Workshops in Computing

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