Poset Description of Grid Features and Application to Off-Line Signature Verification

This work introduces a novel representation for the off-line handwritten signature by measuring its structural characteristics with a set of partially ordered grid features. Thirty-two binary symbols are delineated within the five-by-five pixel window and considered to be the alphabet of a probabilistic source. Subsequently and for practical purposes the whole set is appropriately organized into subsets of four symbols each. The new arrangement is used to detect the presence of simple or compound symbols in the signature image. The utilization of the partially ordered set or poset notion, intuitively arranges the binary feature extraction masks into first order chains, creating in this way a first order probabilistic description of the signature's structure that is characteristic of the motoric signature generating process. In order to estimate these probabilities, the first order searching strategy is limited to pixels neighbors having their grids centered to a predetermined Chebyshev distance of two. The utilized verification strategy relies on an SVM based classifier and the equal error rate figure. Our experimental scheme handles skilled forgery as well and derives verification results for two datasets, the GPDS300 and a proprietary one.