Efficient Computation of Mahalanobis Distance in Financial Hand-Written Chinese Character Recognition

The recognition of hand-written Chinese characters using Mahalanobis distance is extensively utilized in bank cheque processing applications. The Mahalanobis distance, defined by the innovation and its covariance, is compared among several target character classes, and the computation is a time-consuming operation. This paper presents an efficient computation for this process. The method described here can be summarized as an incremental, non-decreasing computation for the Mahalanobis distance; if the incrementally computed value exceeds the threshold then the computation is stopped. The elements of covariance and innovation are only computed if they are used, and progressivity is the major advantage of the method. This method is based upon the square-root-free Cholesky's factorization. Experiment shows the method proposed here is effective in financial hand-written character recognition.