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Proceedings Paper

Selecting the kernel type for a web-based adaptive image retrieval systems (AIRS)
Author(s): Anca Doloc-Mihu; Vijay V. Raghavan
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Paper Abstract

The goal of this paper is to investigate the selection of the kernel for a Web-based AIRS. Using the Kernel Perceptron learning method, several kernels having polynomial and Gaussian Radial Basis Function (RBF) like forms (6 polynomials and 6 RBFs) are applied to general images represented by color histograms in RGB and HSV color spaces. Experimental results on these collections show that performance varies significantly between different kernel types and that choosing an appropriate kernel is important.

Paper Details

Date Published: 16 January 2006
PDF: 12 pages
Proc. SPIE 6061, Internet Imaging VII, 60610H (16 January 2006); doi: 10.1117/12.643677
Show Author Affiliations
Anca Doloc-Mihu, Univ. of Louisiana at Lafayette (United States)
Vijay V. Raghavan, Univ. of Louisiana at Lafayette (United States)


Published in SPIE Proceedings Vol. 6061:
Internet Imaging VII
Simone Santini; Raimondo Schettini; Theo Gevers, Editor(s)

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