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Journal of Electronic Imaging

Saliency field map construction for region-of-interest-based color image querying
Author(s): Mehmet Celenk; Qiang Zhou; Vermund Vetnes; Rakesh K. Godavari
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Paper Abstract

Spectral (color) and spatial (shape) features available in pictures are two significant sources of information for content-based retrieval of image databases. The developed adaptive shape transform approach originated from the premise that a two-dimensional (2-D) shape can be recovered from a set of Radon-transform-based projections. For search consistency, it is necessary to identify the region(s) of interest (ROI) before applying the Radon transform to the shape query. ROIs are detected automatically by means of saliency-map-based segmentation. The Radon transform packs the shape information of a 2-D object along the projection axes of known orientation, and generates a series of one-dimensional (1-D) functions from color channels for projection angles ranging from 0 to 180 deg. The optimal number of projections for a particular shape is determined by imposing the Kullback-Leibler divergence (KLD) distance measure as the similarity metric between the query and database images. The Radon transforms with the shortest and longest lengths yield the most distinctive shape attributes for the object classes being queried and enable the feature space to be invariant to translation and rotation in the spatial plane. The proposed algorithm is tested on a wide range of color images with complex shaped objects and different spatial resolutions. The KLDs between two images are calculated in the longest and shortest directions of the Radon transform, and then are summed together to find the similarity measure between the query and database pictures. Experimental results are close to those that a human observer expects. Further, the method is quite robust and it can account for high image noise (Shao and Celenk, 2001).

Paper Details

Date Published: 1 July 2005
PDF: 9 pages
J. Electron. Imag. 14(3) 033012 doi: 10.1117/1.1993626
Published in: Journal of Electronic Imaging Volume 14, Issue 3
Show Author Affiliations
Mehmet Celenk, Ohio Univ. (United States)
Qiang Zhou, Ohio Univ. (United States)
Vermund Vetnes, Ohio Univ. (United States)
Rakesh K. Godavari, Ohio Univ. (United States)

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