Region-based image querying
Research output: Contribution to journal › Conference article › Research › peer-review
Standard
Region-based image querying. / Carson, Chad; Belongie, Serge; Greenspan, Hayit; Malik, Jitendra.
In: Proceedings - IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997, 1997, p. 42-49.Research output: Contribution to journal › Conference article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Region-based image querying
AU - Carson, Chad
AU - Belongie, Serge
AU - Greenspan, Hayit
AU - Malik, Jitendra
N1 - 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.
PY - 1997
Y1 - 1997
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84959050338&partnerID=8YFLogxK
U2 - 10.1109/IVL.1997.629719
DO - 10.1109/IVL.1997.629719
M3 - Conference article
AN - SCOPUS:84959050338
SP - 42
EP - 49
JO - Proceedings - IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997
JF - Proceedings - IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997
T2 - 1997 IEEE Workshop on Content-Based Access of Image and Video Libraries, CBAIVL 1997
Y2 - 20 June 1997 through 20 June 1997
ER -
ID: 302060820