NDLI: Improving visual recognition using color normalization in digital video applications

Content Provider	IEEE Xplore Digital Library
Author	Sanchez, J.M. Binefa, X.
Copyright Year	2000
Description	Author affiliation: Dept. d'Inf., Univ. Autonoma de Barcelona, Spain (Sanchez, J.M.)
Abstract	Color variations in video imagery caused by imperfections of acquisition devices from analog sources severely penalize the performance of visual recognition tasks, which are very important for smart video indexing, annotation and browsing, for instance. We propose a color correction technique based on modeling the distribution in RGB space of the colors generated by a particular device using a mixture of Gaussian probability density functions, in order to automatically obtain transformations that let us have a normalized representation of color images. It has been tested within the framework of appearance based recognition of video key-frames. In this case, the representation of key-frames consists of their projection into a low dimensional linear subspace given by principal component analysis (PCA), where the matching is done using minimum Euclidean distance. The application of color correction significantly improves the recognition rate, giving nearly optimum results.
Starting Page	1187
Ending Page	1190
File Size	504034
Page Count	4
File Format	PDF
ISBN	0780365364
DOI	10.1109/ICME.2000.871573
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Color Application software Image recognition Indexing Testing Principal component analysis TV Computer vision Gaussian processes Probability density function
Content Type	Text
Resource Type	Article

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