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| year | 2000 | | title | IRM: Integrated Region Matching for Image Retrieval | | abstract |
Content-based image retrieval using region segmentation has been an active research area.
We present IRM (Integrated Region Matching), a novel similarity measure for region-based
image similarity comparison. The targeted image retrieval systems represent an image by a
set of regions, roughly corresponding to objects, which are characterized by features reflecting
color, texture, shape, and location properties. The IRM measure for evaluating overall similarity
between images incorporates properties of all the regions in the images by a region-matching
scheme. Compared with retrieval based on individual regions, the overall similarity approach
reduces the influence of inaccurate segmentation, helps to clarify the semantics of a particular
region, and enables a simple querying interface for region-based image retrieval systems. The IRM
has been implemented as a part of our experimental SIMPLIcity image retrieval system. The
application to a database of about 200,000 general-purpose images shows exceptional robustness
to image alterations such as intensity variation, sharpness variation, color distortions, shape
distortions, cropping, shifting, and rotation. Compared with several existing systems, our system
in general achieves more accurate retrieval at higher speed.
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