Abstract—Offline signature verification is one of most
challenging area of pattern recognition. Many methods have
been introduced in literature to find whether a given signature
is genuine or forgery. In the proposed work, the signature
image is converted into time series data using linear scanning
method and then time series shapelets are identified to
distinguish genuine signatures from forged ones. The shapelets
are time series subsequences which are maximally
representative of a class. To compare the time series data, the
proposed method uses Mahalanobis distance measure. The
experimental results show that the method has great reduction
in equal error rate.
Index Terms—Mahalanobis distance measure, time series data, time series shapelets, signatures.
The authors are with Jawaharlal Nehru Technological University Hyderabad, Hyderabad-500085, Andhra Pradesh, India (e-mail: firstname.lastname@example.org, email@example.com).
Cite: M. Arathi and A. Govardhan, "An Efficient Offline Signature Verification System," International Journal of Machine Learning and Computing vol. 4, no. 6, pp. 533-537, 2014.