Content-based retrieval of visual information

Leiden Repository

Content-based retrieval of visual information

Title: Content-based retrieval of visual information
Author: Oerlemans, Adrianus Antonius Johannes
Publisher: Leiden Institute for Advanced Computer Sciences (LIACS), Faculty of Science, Leiden University
Issue Date: 2011-12-22
Keywords: Content-based image retrieval
Salient points
Similarity measures
Texture classification
Video analysis
Abstract: In this dissertation, I investigate new approaches relevant to content-based image retrieval techniques. First, the MOD paradigm is proposed, a method for detecting salient points in images. These salient points are specifically designed to enhance image retrieval accuracy by maximizing distinctiveness. Second, the multi-dimensional maximum likelihood similarity measure is presented, which removes a critical limitation in prior research in this area and provides an improved method of comparing image features. Third, a texture classification method based on low dimensional constructed texture features is introduced which have very low computational complexity and would be suitable for real time video understanding or interactive search of very large image databases. The new approaches are tested on well respected international test sets containing representative imagery.
Description: Promotor: J.N. Kok, Co-promotor: M.S. Lew
With summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Oerlemans, A.A.J., 2011, Doctoral thesis, Leiden University

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