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020 9781461516415|q(electronic bk.)
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100 1 Wang, James Z.
245 10 Integrated Region-Based Image Retrieval|h[electronic
resource] /|cby James Z. Wang.
260 Boston, MA :|bSpringer US,|c2001.
300 1 online resource (xiv, 178 pages).
338 online resource|bcr|2rdacarrier
490 1 The Information Retrieval Series,|x1387-5264 ;|v11
520 The need for efficient content-based image retrieval has
increased tremendously in areas such as biomedicine,
military, commerce, education, and Web image
classification and searching. In the biomedical domain,
content-based image retrieval can be used in patient
digital libraries, clinical diagnosis, searching of 2-D
electrophoresis gels, and pathology slides. Integrated
Region-Based Image Retrieval presents a wavelet-based
approach for feature extraction, combined with integrated
region matching. An image in the database, or a portion of
an image, is represented by a set of regions, roughly
corresponding to objects, which are characterized by color,
texture, shape, and location. A measure for the overall
similarity between images is developed as a region-
matching scheme that integrates properties of all the
regions in the images. The advantage of using this "soft
matching" is that it makes the metric robust to poor
segmentation, an important property that previous research
has not solved. Integrated Region-Based Image Retrieval
demonstrates an experimental image retrieval system called
SIMPLIcity (Semantics-sensitive Integrated Matching for
Picture LIbraries). This system validates these methods on
various image databases, proving that such methods perform
much better and much faster than existing ones. The system
is exceptionally robust to image alterations such as
intensity variation, sharpness variation, intentional
distortions, cropping, shifting, and rotation. These
features are extremely important to biomedical image
databases since visual features in the query image are not
exactly the same as the visual features in the images in
the database. Integrated Region-Based Image Retrieval is
an excellent reference for researchers in the fields of
image retrieval, multimedia, computer vision and image
650 0 Computer science.
650 0 Data structures (Computer science)
650 0 Information storage and retrieval systems.
650 0 Computer vision.
650 0 Computer industry.
655 4 Electronic books.
776 08 |iPrint version:|z9781461356554
830 0 Information retrieval series ;|v11.
856 40 |3SpringerLink|uhttp://dx.doi.org.ezp.lib.unimelb.edu.au/
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