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Proceedings Paper

BlobContours: adapting Blobworld for supervised color- and texture-based image segmentation
Author(s): Thomas Vogel; Dinh Quyen Nguyen; Jana Dittmann
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Paper Abstract

Extracting features is the first and one of the most crucial steps in recent image retrieval process. While the color features and the texture features of digital images can be extracted rather easily, the shape features and the layout features depend on reliable image segmentation. Unsupervised image segmentation, often used in image analysis, works on merely syntactical basis. That is, what an unsupervised segmentation algorithm can segment is only regions, but not objects. To obtain high-level objects, which is desirable in image retrieval, human assistance is needed. Supervised image segmentations schemes can improve the reliability of segmentation and segmentation refinement. In this paper we propose a novel interactive image segmentation technique that combines the reliability of a human expert with the precision of automated image segmentation. The iterative procedure can be considered a variation on the Blobworld algorithm introduced by Carson et al. from EECS Department, University of California, Berkeley. Starting with an initial segmentation as provided by the Blobworld framework, our algorithm, namely BlobContours, gradually updates it by recalculating every blob, based on the original features and the updated number of Gaussians. Since the original algorithm has hardly been designed for interactive processing we had to consider additional requirements for realizing a supervised segmentation scheme on the basis of Blobworld. Increasing transparency of the algorithm by applying usercontrolled iterative segmentation, providing different types of visualization for displaying the segmented image and decreasing computational time of segmentation are three major requirements which are discussed in detail.

Paper Details

Date Published: 17 January 2006
PDF: 12 pages
Proc. SPIE 6073, Multimedia Content Analysis, Management, and Retrieval 2006, 60730I (17 January 2006); doi: 10.1117/12.650742
Show Author Affiliations
Thomas Vogel, Otto-von-Guericke Univ. Magdeburg (Germany)
Dinh Quyen Nguyen, Otto-von-Guericke Univ. Magdeburg (Germany)
Jana Dittmann, Otto-von-Guericke Univ. Magdeburg (Germany)

Published in SPIE Proceedings Vol. 6073:
Multimedia Content Analysis, Management, and Retrieval 2006
Edward Y. Chang; Alan Hanjalic; Nicu Sebe, Editor(s)

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