If two vectors originate from the same underlying distribution, the distance
between them could be computed with the Mahalanobis distance, a generalization of the
Euclidean one. Also, it can be defined as the Euclidean distance computed in the
Mahalanobis space. Moreover, there exist also the city block-based Mahalanobis
distance and other versions including the angle- and cosine-based ones. Largely
employed for face recognition with bi-dimensional facial data, Mahalanobis gains very
good performances with PCA algorithms.
Keywords: Mahalanobis distance, Mahalanobis angle, Mahalanobis cosine
measure.
