Content-based Access in Image Database by Quantitative Relationships
In this paper, we describe a novel technique to perform content-based access in image databases using quantitative spatial relationships. Usually, spatial relation-based indexing methods fail if the metric spatial information contained in the images must be preserved. In order to provide a more robu...
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| Published in: | Journal of visual languages and computing Vol. 11; no. 5; pp. 573 - 589 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
2000
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| ISSN: | 1045-926X |
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| Abstract | In this paper, we describe a novel technique to perform content-based access in image databases using quantitative spatial relationships. Usually, spatial relation-based indexing methods fail if the metric spatial information contained in the images must be preserved. In order to provide a more robust approach to directional relations indexing with respect to metric differences in images, this paper introduces an improvement of the virtual image index, namely quantitative virtual image, using a quantitative methodology. A scalar quantitative measure is associated with each spatial relation, in order to discriminate among images of the image database having the same objects and spatial relationships, but different degree of similarity if we also consider distance relationships. The measure we introduce does not correspond to any significant increase of complexity with respect to the standard virtual image providing a more precise answer set. |
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| AbstractList | In this paper, we describe a novel technique to perform content-based access in image databases using quantitative spatial relationships. Usually, spatial relation-based indexing methods fail if the metric spatial information contained in the images must be preserved. In order to provide a more robust approach to directional relations indexing with respect to metric differences in images, this paper introduces an improvement of the virtual image index, namely quantitative virtual image, using a quantitative methodology. A scalar quantitative measure is associated with each spatial relation, in order to discriminate among images of the image database having the same objects and spatial relationships, but different degree of similarity if we also consider distance relationships. The measure we introduce does not correspond to any significant increase of complexity with respect to the standard virtual image providing a more precise answer set. |
| Author | TUCCI, MAURIZIO CIBELLI, MAURIZIO NAPPI, MICHELE |
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| Cites_doi | 10.1109/32.245741 10.1080/02693799108927841 10.1006/jvlc.1998.0091 10.1016/S0262-8856(98)00186-3 10.1109/TPAMI.1987.4767923 10.1109/69.536246 10.1145/182.358434 10.1145/201040.201041 10.1109/69.599932 |
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Retrieval of pictures using approximate matching publication-title: Proceedings of the Multimedia Database System: Issues and Research Direction – volume: 19 start-page: 997 year: 1993 end-page: 1011 ident: RF3 article-title: A three-dimensional iconic environment for image database querying publication-title: IEEE Transactions on Software Engineering – volume: 9 start-page: 435 year: 1997 end-page: 447 ident: RF6 article-title: Similarity searching in medical image databases publication-title: IEEE Transactions on Knowledge and Data Engineering – year: 1997 ident: RF7 article-title: Dimensional reasoning with qualitative and quantitative distances publication-title: Proceedings of AAAI-97 Workshop on Spatial and Temporal Reasoning – volume: 9 start-page: 567 year: 1998 end-page: 596 ident: RF14 article-title: Pictorial query specification for browsing through spatially-referenced image databases publication-title: Journal of Visual Languages and Computing – start-page: 43 year: 1996 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10.1006/jvlc.2000.0171_RF12 article-title: Point-set topological spatial relations publication-title: International Journal of Geographical Information Systems doi: 10.1080/02693799108927841 – year: 1996 ident: 10.1006/jvlc.2000.0171_RF4 article-title: Symbolic projection for image information retrieval and spatial reasoning – volume: 9 start-page: 567 year: 1998 ident: 10.1006/jvlc.2000.0171_RF14 article-title: Pictorial query specification for browsing through spatially-referenced image databases publication-title: Journal of Visual Languages and Computing doi: 10.1006/jvlc.1998.0091 – volume: 17 start-page: 969 year: 1999 ident: 10.1006/jvlc.2000.0171_RF1 article-title: IME: An image management environment with content based access publication-title: Image and Vision Computing doi: 10.1016/S0262-8856(98)00186-3 – volume: 9 start-page: 413 year: 1987 ident: 10.1006/jvlc.2000.0171_RF2 article-title: Iconic indexing by 2-D string publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.1987.4767923 – volume: 8 start-page: 533 year: 1996 ident: 10.1006/jvlc.2000.0171_RF10 article-title: Picture similarity retrieval using the 2D projection interval representation publication-title: IEEE Transaction on Knowledge and Data Engineering doi: 10.1109/69.536246 – start-page: 449 year: 1996 ident: 10.1006/jvlc.2000.0171_RF15 article-title: Distances for uncertain topological relations – volume: 26 start-page: 832 year: 1983 ident: 10.1006/jvlc.2000.0171_RF11 article-title: Maintaining knowledge about temporal intervals publication-title: Communications of the ACM doi: 10.1145/182.358434 – volume: 13 start-page: 115 year: 1995 ident: 10.1006/jvlc.2000.0171_RF8 article-title: Design and evaluation of algorithms for image retrieval by spatial similarity publication-title: ACM Transactions on Information Systems doi: 10.1145/201040.201041 – volume: 9 start-page: 435 year: 1997 ident: 10.1006/jvlc.2000.0171_RF6 article-title: Similarity 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