STRUCTURAL INTERPRETATION OF HANDWRITTEN SIGNATURE IMAGES

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Abstract
The interpretation of handwritten signature images should be closely related to the writer’s identity. The representation and analysis of the handwritten signature is the major challenge in the field of automatic signature verification. A new concept of representation and interpretation of handwritten signature images is advocated. The segmentation process breaks up the signature into a collection of arbitrarily-shaped primitives. In the next step, a local interpretation process serves as a sophisticated template matching, permitting the labeling of all primitives from the test primitive set. This is followed by the global interpretation process, which permits the evaluation of a similarity measure between two structural graphs. Experimental results obtained from a database of 800 handwritten signature images from 20 writers show a performance with a type I error rate of ∈1=1.50%, a type II error rate of ∈2=1.37% and a total error rate ∈t=1.43% in the best strategy proposed using a minimum-distance classifier and two reference signatures. A complete description of this novel automatic handwritten signature verification system is presented in this paper.

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