@inproceedings{c3eb16ce831b44e4b904cb542f70cc0a,
title = "Reducing the dimension of color features using a na{\"i}ve Bayesian classifier",
abstract = "Color histograms are usually used as the color feature vectors for classifying the color of objects in images. We reduce the dimension of the feature vector by a factor of about 30 by using a na{\"i}ve Bayesian classifier, and use the resulting feature vectors with a support vector machine to recognize vehicle colors. Experiments show that the recognition rate is close to that achieved with the original large feature vectors, while recognition time is reduced by a factor of more than 30. We also show that our method outperforms principal component analysis.",
keywords = "Bayesian classifier, Color histogram, Component, Dimension reduction",
author = "Park, {Sun Mi} and Kim, {Ku Jin}",
year = "2009",
doi = "10.1109/ICUT.2009.5405735",
language = "English",
isbn = "9781424451302",
series = "Proceedings of the 4th International Conference on Ubiquitous Information Technologies and Applications, ICUT 2009",
booktitle = "Proceedings of the 4th International Conference on Ubiquitous Information Technologies and Applications, ICUT 2009",
note = "4th International Conference on Ubiquitous Information Technologies and Applications, ICUT 2009 ; Conference date: 20-12-2009 Through 22-12-2009",
}