Blobworld: Image segmentation using Expectation-Maximization and its application to image querying (1999)
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| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Citations: | 265 - 8 self |
BibTeX
@ARTICLE{Carson99blobworld:image,
author = {Chad Carson and Serge Belongie and Hayit Greenspan and Jitendra Malik},
title = {Blobworld: Image segmentation using Expectation-Maximization and its application to image querying},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {1999},
volume = {24},
pages = {1026--1038}
}
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Abstract
Retrieving images from large and varied collections using image content as a key is a challenging and important problem. 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. This "Blobworld" representation is created by clustering pixels in a joint color-texture-position feature space. The segmentation algorithm is fully automatic and has been run on a collection of 10,000 natural images. We describe a system that uses the Blobworld representation to retrieve images from this collection. An important aspect of the system is that 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, query results from these systems can be inexplicable, despite the availability of knobs for adjusting the similarity metrics. By finding image regions whi...
