Dissimilarity Computation through Low Rank Corrections for Content-Based Access
نویسندگان
چکیده
We present a general methodology for indexing with multivariate features based on the Bhattacharyya distance, which takes into account both the mean-di erence and the covariancedi erence between two distributions. To reduce the amount of computations and the size of logical database entry, we approximate the Bhattacharyya distance in the low dimensional subspace of the rst few principal components. The retrieval performance was assessed for three texture databases (VisTex, Brodatz, and MeasTex) and two texture representations (MRSAR model and Gabor features), and was consistently superior to the Mahalanobis distance based approaches. The MRSAR representation yielded better performance than the Gabor features.
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