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      Touchscreen User Interface Design for Content Based Image Retrieval

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      Electronic Visualisation and the Arts (EVA 2017) (EVA)

      Electronic Visualisation and the Arts

      11 – 13 July 2017

      CBIR, User Interface, Touch Screen, Image extraction

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The interface presented combines query-by-sketch and query-by-image modes of interaction. It is designed to harmonise extraction of several basic shape descriptors with 2d haptic pointing.

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          Most cited references 5

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          A survey of content-based image retrieval with high-level semantics

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            Content-Based Image Retrieval over the Web Using Query by Sketch and Relevance Feedback

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              Object extraction as a basic process for content-based image retrieval (CBIR) system

               T. Jaworska (2007)
              This article describes the way in which image is prepared for content-based image retrieval system. Automated image extraction is crucial; especially, if we take into consideration the fact that the feature selection is still a task performed by human domain experts and represents a major stumbling block in the process of creating fully autonomous CBIR systems. Our CBIR system is dedicated to support estate agents. In the database, there are images of houses and bungalows. We put all our efforts into extracting elements from an image and finding their characteristic features in the unsupervised way. Hence, the paper presents segmentation algorithm based on a pixel colour in RGB colour space. Next, it presents the method of object extraction applied to obtain separate objects prepared for the process of introducing them into database and further recognition. Moreover, we present a novel method of texture identification which is based on wavelet transformation. Due to the fact that the majority of texture is geometrical (such as bricks and tiles) we have used the Haar wavelet. After a set of low-level features for all objects is computed, the database is stored with these features.
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                Author and article information

                Contributors
                Conference
                July 2017
                July 2017
                : 315-316
                Affiliations
                AGH University of Science and Technology

                Krakow, Poland
                University of Bielsko-Biała

                Bielsko-Biała, Poland
                Article
                10.14236/ewic/EVA2017.64
                © Olszewska et al. Published by BCS Learning and Development Ltd. Proceedings of EVA London 2017, 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/

                Electronic Visualisation and the Arts (EVA 2017)
                EVA
                London, UK
                11 – 13 July 2017
                Electronic Workshops in Computing (eWiC)
                Electronic Visualisation and the Arts
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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