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Volume: 2 | Article ID: art00068
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Image Retrieval using Spatial Chromatic Histograms
P. Lambert
N. Hervey
H. Grecu
  DOI :  10.2352/CGIV.2004.2.1.art00068  Published Online :  January 2004
Abstract

In this work, a new method for color image indexation is proposed. First the color space and the spatial domain are both projected on a 1D space and partitioned in a fuzzy way. Then, the 2D histogram of the membership degrees to these two partitions is computed. This histogram can be used to index each image of a large database. Therefore, retrieval is simply performed by computing the Euclidean difference between the 2D histogram of the query image and the 2D histogram of a database image. This method is applied on a real database.

Journal Title : Conference on Colour in Graphics, Imaging, and Vision
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
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 DOI 10.2352/CGIV.2004.2.1.art00068
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P. Lambert, N. Hervey, H. Grecu, "Image Retrieval using Spatial Chromatic Histograms"  in Proc. IS&T CGIV 2004 Second European Conf. on Colour in Graphics, Imaging, and Vision,  2004,  pp 343 - 347,  https://doi.org/10.2352/CGIV.2004.2.1.art00068

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  Copyright statement 
Copyright © Society for Imaging Science and Technology 2004
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2158-6330(20040101)2004:1L.343;1-
cgiv_v2004n1/splitsection68.xml
/ist/cgiv/2004/00002004/00000001/art00068
Articles
Image Retrieval using Spatial Chromatic Histograms
LambertP.
HerveyN.
GrecuH.
01012004
2004
1
343
347
2004
In this work, a new method for color image indexation is proposed. First the color space and the spatial domain are both projected on a 1D space and partitioned in a fuzzy way. Then, the 2D histogram of the membership degrees to these two partitions is computed. This histogram can be used to index each image of a large database. Therefore, retrieval is simply performed by computing the Euclidean difference between the 2D histogram of the query image and the 2D histogram of a database image. This method is applied on a real database.