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Cited by 474

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Color- and texture-based image segmentation using EM and its application to content-based image retrieval

Belongie, S., Carson, C., Greenspan, H., Malik, J.·2002·Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)

Abstract

Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present a new image representation which provides a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. This so-called "blobworld" representation is based on segmentation using the expectation-maximization algorithm on combined color and texture features. The texture features we use for the segmentation arise from a new approach to texture description and scale selection. We describe a system that uses the blobworld representation to retrieve images. An important and unique aspect of the system is that, in the context of similarity-based querying, the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer the user this view into the workings of the system; consequently, the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.

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Crossref · 10.1109/iccv.1998.710790

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Metadata

Authors
Belongie, S., Carson, C., Greenspan, H., & Malik, J.
Venue
Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)
Published
2002-11-27
Pages
675-682
OpenAlex
W2171096036
Cited by
474
References
21
FWCI
32.17
Type
conference paper
Language
en
Open access
closed

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