Abstract
This paper presents a novel hybrid approach for visual information retrieval (VIR) that combines shape analysis of objects in image with their indexing by textual descriptions. The principal goal of presented technique is applying Two Segments Turning Function (2STF) proposed by authors for efficient invariant to spatial variations shape processing and implementation of semantic Web approaches for ontology-based user-oriented annotations of multimedia information. In the proposed approach the user’s textual queries are converted to image features, which are used for images searching, indexing, interpretation, and retrieval. A decision about similarity between retrieved image and user’s query is taken computing the shape convergence to 2STF combining it with matching the ontological annotations of objects in image and providing in this way automatic definition of the machine-understandable semantics. In order to evaluate the proposed approach the Image Retrieval by Ontological Description of Shapes system has been designed and tested using some standard image domains.
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References
O. Starostenko, A. Chévez-Aragón, G. Burlak, R. Contreras, “A Novel Star Field Approach for Shape Indexing in CBIR System”,J. of Eng. Letters, vol. , Oct. 2007, pp. 10-21.
A. Chévez-Aragon, O. Starostenko, L. Flores-Pulido, “Star Fields: Improvements in Shape-Based Image Retrieval”,J. Research on Comp. Science, vol. 27, 2007, p.79-90.
T. Gevers, A. W. Smeulders, “Combining color and shape invariant features for image retrieval”,IEEE Trans. on Image Proces., vol. 9, (1), 2000, pp. 102-119.
O. Starostenko, A. Chévez-Aragón, A. Zehe, G. Burlak, “A Novel Shape and Ontological Indexing for VIR Systems”, 12th Americas Conf. on Inf. Systems, USA, Aug. 2006, pp. 2833-2842.
D. Fensel,Ontologies: a silver bullet for knowledge management and electronic commerce, USA: Springer, 2nd ed., 2004.
QBICTM (2006, May, 10). IBM’s Query by image content, Available: http://wwwqbic.almaden.ibm.com/
Amore (2006, Feb.,1). Advance multimedia oriented retrieval engine, Available: http://www.ariadne.ac.uk/issue9/web-focus
Q. Iqbal, (2007, May, 10). Content Based Image REtrieval System, Comp and Vision Research Center, Un. of Texas at Austin, Ph.D, [Online]. Available: http://amazon.ece.utexas.edu/~qasim/research.htm
O. Starostenko, A. Chévez-Aragón, “A Hybrid Approach for Image Retrieval with Ontological Content-Based Indexing”,Lecture Notes, Progress in Pattern recognition, Springer-Verlag, vol.. 3773, 2005, pp. 997-1004.
A. Del Bimbo, P. Pala, “Visual image retrieval by elastic matching of user sketche”,IEEE Trans. Pattern Analysis Mach. Intell. vol. 19 (2), 1997, pp. 121–132.
F. Mokhtarian, “A theory of multiscale, curvature-based shape representation for planar curves”,IEEE Trans. On Pattern Analysis Mach Intell., vol. 14 (8), 1992, pp. 789-805.
O. Starostenko, A.Chavez-Aragon, J. Sénchez, R. Rosas, “Content Based Visual Information Retrieval For Management Information Systems”,European. and Mediterranean Conf. on Inf. Sytems, June, Spain, 2007, pp.1-7.
J. R. Ohm, F. B. Bunjamin, W. Liebsch, B. Makai, K. Muller, A. Somlic, D. Zier, “A set of visual feature descriptors and their combination in a low-level description scheme”,J. Signal Process. Image Commun., vol. 16, 2000, pp. 157–179.
A. Chévez-Aragón, ASemantic Image Information Retrieval Model, Ph.D Technical report, University UDLA-P, Mexico, 2006.
M. S. Lew,Principles of visual information retrieval, Advances in pattern recognition, USA: Springer-Verlag, 2001.
M. Arkin, L. P. Chew, “An efficiently computable metric for comparing polygonal shapes”,J. EEE trans, vol. 13, 1991, pp. 209-206.
M. Osorio, J. A. Navarro Pérez, J. R. Arrazola Ramírez, V. Borja Macías, “Logics with Common Weak Completions”,Oxford J. of Logic and Computation, vol. 16 (6) 2006, pp. 867-890.
T. R. Gruber, “A translation approach to portable ontology specifications”,J. Knowledge Acquisition, 1993, pp. 199-220.
N. Guarino, “Semantic Matching: Formal Ontological Distinctions for Information Organization, Extraction, and Integration”,Lecture Notes in Comp. Science, vol. 1299, Springer, 1997, pp. 139-170.
D. Beckett, “The design and implementation of the Redland RDF application framework”, 10th Int. WWW Conf., 2001, pp. 120-125.
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Starostenko, O., Rodríguez-Asomoza, J., Sénchez-López, S., Chévez-Aragón, J. (2008). Shape Indexing and Retrieval: A Hybrid Approach Using Ontological Descriptions. In: Elleithy, K. (eds) Innovations and Advanced Techniques in Systems, Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8735-6_72
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DOI: https://doi.org/10.1007/978-1-4020-8735-6_72
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