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標題: 基於空間關係之語意影像搜尋系統
Semantic Image Search Based on Spatial Relationships
作者: 孟憲君 
Meng, Shian-Jiun 
關鍵字: Semantic web;語意網;Image search;OWL;WordNet;Ontology;影像搜尋;OWL;詞彙網路;本體論
出版社: 資訊科學系所
引用: [1] Alexander Maedche and Steffen Staab, “Ontology Learning for the Semantic Web”, IEEE INTELLIGENT SYSTEMS, 2001. [2] E.L. van den Broek, L.G. Vuurpijl, P. Kisters, and J.C.M. von Schmid ,“Content-Based Image Retrieval: Color-selection exploited”, Nijmegen Institute for Cognition and Information, 2002. [3] A.Th.(Guus) Schreiber, Barbara Dubbeldam, Jan Wielemaker, and Bob ielinga, “Ontology-Based Photo Annotation”, IEEE INTELLIGENT SYSTEMS, 2001. [4] Director of the World Wide Web Consortium, [5] Michael C. Daconta, Leo J. Obrst and Kevin T. Smith, “The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management”, pp.9-15,ISBN:0471432571. [6] Graham Klyne and Jeremy Carroll, “Resource Description Framework (RDF) Concepts and Abstract Syntax”, W3C Proposed Recommendation,, January 23, 2003. [7] Deborah McGuinness and Frank van Harmelen, “OWL Web Ontology Language Overview”, W3C Proposed Recommendation, , August 18, 2003. [8] Jena - A Semantic Web Framework for Java, [9] Irena Valova, Boris Rachev, “Retrieval by Color Features in Image Databases”, Budapest, Hungary, Septemper, 2004. [10] Picture Finder Online-Demo, [11] A.Th.(Guus) Schreiber, Barbara Dubbeldam, Jan Wielemaker, and Bob ielinga, “Ontology-Based Photo Annotation”, IEEE INTELLIGENT SYSTEMS, 2001. [12] A.M. Tam and C.H.C. Leung, “Structured Natural- Language Description for Semantic Content Retrieval”, J. American Soc. Information Science, Sept. 2001. [13] Laura Hollink, Guus Schreiber, Jan Wielemaker, “Semantic Annotation of Image Collections”, Proceedings of the K-CAP 2003 Workshop on Knowledge Markup, 2003. [14] Eero Hyvonen, Hannu Erki, “Ontology-Based Image Annotation and Retrieval”, University of Helsinki Dept. of Computer Science Helsinki 27th April 2005. [15] A lexical database for the English language, [16] Lei Zhang, Fuzong Lin, Bo Zhang,“SUPPORT VECTOR MACHINE LEARNING FOR IMAGE RETRIEVAL”, Department of Computer Science and Technology, Tsinghua University, Beijing, 2001. [17] Zaher AGHBARI, Akifumi MAKINOUCHI, “Semantic Approach to Image Database Classification and Retrieval”, E.E., Kyushu University, 2003. [18] Y.Deng, B.S.Manjunath and H.Shin , "Color Image Segmentation", Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR ''99, Fort Collins, CO, vol.2, pp.446-51, June 1999. [19] JSEG algorithm, [20] DAMIAN CONWAY, “An Experimental Comparison of Three Natural Language Colour Naming Models”, Proc. East- West International Conference on Human-Computer Interaction, St. Petersburg, Russia, pp. 328-39, 1992. [21] WordNet API,

As the volume of multimedia images increase drastically on the web, it is important and becoming difficult to search for a targeted picture efficiently. Commonly used content-based image retrieval is short of semantic support. The retrieved resources may be far away from user''s expectation. In this paper, we propose a new image retrieval system incorporated semantics to make the system better in image repository, consequently, to search for an image more accurate.
Based on the construction of spatial ontology, we implement a semi-automatic annotation images system. Firstly, images are segmented according to the variations in color. We extract each segmented region, record its color feature and make annotations in the ontology file. Accordingly, we are able to apply the spatial relationships from the established ontology along with synonym and hypernym characteristics from the WordNet for efficient image retrieved. Finally we compare and report the performance of three different searching mechanisms: keyword-based, spatial relationship-based, and simple natural language and action behavior relationship-based.
其他識別: U0005-0307200617243700
Appears in Collections:資訊科學與工程學系所

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