Color-based image retrieval using binary signatures
Proceedings of the 2002 ACM symposium on Applied computing
Image indexing and retrieval using signature trees
Data & Knowledge Engineering
A Prototype Content-Based Retrieval System that Uses Virtual Images to Save Space
Proceedings of the 27th International Conference on Very Large Data Bases
A Color Image Retrieval Method Based on Local Histogram
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Query by image and video content: a colored-based stochastic model approach
Data & Knowledge Engineering
Image retrieval using color component analysis
ISICT '04 Proceedings of the 2004 international symposium on Information and communication technologies
International Journal of Intelligent Systems Technologies and Applications
Wildlife video key-frame extraction based on novelty detection in semantic context
Multimedia Tools and Applications
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Image indexing is the process of image retrieval from databases of images or videos based on their contents. Specifically, histogram-based algorithms are considered to be effective for color image indexing. We suggest a new method of color space quantization in the CIELUV color space, named weighted LUV quantization. With this method, each bin in the LUV space has a different weighting factor, which is applied to the histogram intersection.The weighted LUV histogram intersection provides the advantage of perceptual uniformity of the CIELUV color space. An additional advantage is the consideration of perceptual sensitivity to more saturated colors by the use of a weighting factor.