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      A Novel Architecture for Trademark Image Retrieval Systems

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      Challenge of Image Retrieval (CIR)

      Image Retrieval

      5 February 1998

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            Abstract

            This paper describes the first phase of an ongoing research project aimed at implementing a trademark retrieval system using an associative memory neural network. The novel aspect of the work described in this paper is the presentation of a new integrated methodology for employing multiple interpretations from different analytical levels of images for image retrieval. In achieving this objective, we extract local features as well as features of the closed figures of images. In deriving alternative interpretations of the images, a segment level gestalt grouping method based on a modification of Sarkar and Boyer’s method is used. 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 may feasibly be implemented using an associative memory neural network to achieve high performance in retrieval.

            Content

            Author and article information

            Contributors
            Conference
            February 1998
            February 1998
            : 1-16
            Affiliations
            [0001]Department of Computer Science

            University of York

            York, Y01 5DD, UK
            Article
            10.14236/ewic/CIR1998.10
            0ddbe0ee-1d71-4f48-a51c-a587fad0c25f
            © Sujeewa Alwis et al. Published by BCS Learning and Development Ltd. Challenge of Image Retrieval, University of Northumbria at Newcastle, UK

            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
            University of Northumbria at Newcastle, UK
            5 February 1998
            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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