DocumentCode :
798629
Title :
Efficient color histogram indexing for quadratic form distance functions
Author :
Hafner, James ; Sawhney, Harpreet S. ; Equitz, Will ; Flickner, Myron ; Niblack, Wayne
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
Volume :
17
Issue :
7
fYear :
1995
fDate :
7/1/1995 12:00:00 AM
Firstpage :
729
Lastpage :
736
Abstract :
In image retrieval based on color, the weighted distance between color histograms of two images, represented as a quadratic form, may be defined as a match measure. However, this distance measure is computationally expensive and it operates on high dimensional features (O(N)). We propose the use of low-dimensional, simple to compute distance measures between the color distributions, and show that these are lower bounds on the histogram distance measure. Results on color histogram matching in large image databases show that prefiltering with the simpler distance measures leads to significantly less time complexity because the quadratic histogram distance is now computed on a smaller set of images. The low-dimensional distance measure can also be used for indexing into the database
Keywords :
computational complexity; image colour analysis; image matching; indexing; information retrieval; query processing; visual databases; color based image retrieval; color distributions; color histogram indexing; feature matching; image databases; image querying; low dimension distance measure; lower bounds; match measure; quadratic form distance functions; time complexity; Character recognition; Computational complexity; Computer vision; Data mining; Feature extraction; Histograms; Indexing; Machine vision; Pattern analysis; Pattern recognition;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.391417
Filename :
391417
Link To Document :
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