The Mahalanobis distance is based on the covariance among variables in the feature vectors which are compared. It has the advantage of utilizing group means and variances for each variable and the problems of scale and correlation inherent in the Euclidean distance are no longer an issue. When using Euclidean distance, the set of points equidistant from a given location is a sphere. The Mahalanobis distance stretches this sphere to correct the respective scales of different variables and to account for correlation among variables.
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(2009). Mahalanobis Distance. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_865
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DOI: https://doi.org/10.1007/978-0-387-73003-5_865
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