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This paper proposes a new notion distance on the CBIR process whichis derived from the measure of multivariate dispersion called vector variance (VV).The minimum vector variance (MVV) estimator is robust estimator having the highbreakdown point. The CBIR is a retrieval technique using the visual informationby retrieving collections of digital images. The process of retrieval is carried outby measuring the similarity between query image and the image in the databasethrough similarity measure. Distance is a metric often used as similarity measureon CBIR. The query image is relevant to an image in the database if the value ofsimilarity measure is 'small'. This means that a good CBIR retrieval system mustbe supported by an accurate similarity measure. The classical distance is generatedfrom the arithmetic mean which is vulnerable to the masking e®ect. The appearanceof extreme data causes the in°ation of deviation of the arithmetic mean, this impliesthe distance between the extreme data or the outlier becomes closer than it supposedto be. In the end of section we discuss the high performance of the MVV robustdistance to CBIR process.



High Breakdown Point Image Retrieval Query image Similarity Measure Image Visual Content

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How to Cite
Herwindiati, D. E., Isa, S. M., & Sagara, R. (2010). THE NEW NOTION DISTANCE OF CONTENT BASED IMAGE RETRIEVAL (CBIR). Journal of the Indonesian Mathematical Society, 16(1), 51–67.