Region-based image querying
Research output: Contribution to journal › Conference article › Research › peer-review
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 localized coherent regions 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.
Original language | English |
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Journal | Proceedings - IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997 |
Pages (from-to) | 42-49 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 1997 |
Externally published | Yes |
Event | 1997 IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997 - San Juan, United States Duration: 20 Jun 1997 → 20 Jun 1997 |
Conference
Conference | 1997 IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997 |
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Country | United States |
City | San Juan |
Period | 20/06/1997 → 20/06/1997 |
Sponsor | IEEE Computer Society Technical Committee on PAM1 |
Bibliographical note
Funding Information:
This work was supported by an NSF Digital Library Grant (IRI 94-11334) and NSF graduate fellowships for Serge Belongie and Chad Carson.
Funding Information:
‘This work was supported by an NSF Digital Library Grant (IRI 94- 1 1334) and NSF graduate fellowships for Serge Belongie and Chad Carson.
Publisher Copyright:
© 1997 IEEE.
ID: 302060820