Measurement of the correlation in a multidimensional feature space

This paper introduces an index which can be used as a measure of correlation between features of a multidimensional feature vector. The proposed index has been intuitively explained using constant distance loci of Mahalanobis metric. More rigorous explanation has been given using orthogonal decomposition of the vector space. The application of the proposed index has been given using 2D synthetic data.