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SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries (2001)
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| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Citations: | 551 - 35 self |
BibTeX
@ARTICLE{Wang01simplicity:semantics-sensitive,
author = {James Z. Wang and Jia Li and Gio Wiederhold},
title = {SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2001},
volume = {23},
pages = {947--963}
}
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Abstract
The need for efficient content-based image retrieval has increased tremendously in many application areas such as biomedicine, military, commerce, education, and Web image classification and searching. We present here SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries), an image retrieval system, which uses semantics classification methods, a wavelet-based approach for feature extraction, and integrated region matching based upon image segmentation. As in other regionbased retrieval systems, an image is represented by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. The system classifies images into semantic categories, such as textured-nontextured, graphphotograph. Potentially, the categorization enhances retrieval by permitting semantically-adaptive searching methods and narrowing down the searching range in a database. A measure for the overall similarity between images is developed using a region-matching scheme that integrates properties of all the regions in the images. Compared with retrieval based on individual regions, the overall similarity approach 1) reduces the adverse effect of inaccurate segmentation, 2) helps to clarify the semantics of a particular region, and 3) enables a simple querying interface for region-based image retrieval systems. The application of SIMPLIcity to several databases, including a database of about 200,000 general-purpose images, has demonstrated that our system performs significantly better and faster than existing ones. The system is fairly robust to image alterations.
Keyphrases
picture library semantics-sensitive integrated matching regionbased retrieval system image segmentation efficient content-based image retrieval feature extraction general-purpose image image retrieval system overall similarity semantics classification method wavelet-based approach categorization enhances retrieval particular region many application area inaccurate segmentation image alteration region-based image retrieval system semanticssensitive integrated matching integrated region semantic category individual region overall similarity approach region-matching scheme simple querying interface web image classification adverse effect several database
