Abstract
A method for offline signature verification is presented in this paper. It is based on the segmentation of thesignature skeleton (through standard image skeletonization) into unambiguous sequences of points, or unambiguously connected skeleton segments corresponding to vectorial representations of signature portions. These segments are assumed to be the fundamental carriers of useful information for authenticity verification,and are compactly encoded as sets of 9 scalars (4 sampled coordinates and 1 length measure). Thus signature authenticity is inferred through Euclidean distance based comparisons between pairs of such compact representations. The average performance of this method is evaluated through experiments with offline versions of signatures from the MCYT-100 database. For comparison purposes, three other approaches are applied to the same set of signatures, namely: (1) a straightforward approach based on Dynamic Time Warping distances between segments, (2) a published method by [18], also based on DTW, and (3) the average human performance under equivalent experimental protocol. Results suggest that if human performance is taken as agoal for automatic verification, then we should discard signature shape details to approach this goal. Moreover, our best result – close to human performance – was obtained by the simplest strategy, where equal weights were given to segment shape and length.
Highlights
H ANDWRITTEN signature is a form of personal identification widely accepted, both socially and legally, and it has been used for centuries to authenticate documents such as bank checks, letters, contracts and many other that require proof of authorship
To provide a comparison scenario for the proposed methods based on UCSS, we included in E1 the method published in [29], which extracts projections of bitmaps corresponding to signatures, and compare them through a modified Dynamic Time Warping (DTW), where so called stability measures are included to improve performances
Experiment E2 yielded a Mean Opinion Score (MOS) from 239 cards filled by 103 volunteers, and after comparing all provided labels to the true hidden labels, the estimated MOS was:
Summary
H ANDWRITTEN signature is a form of personal identification widely accepted, both socially and legally, and it has been used for centuries to authenticate documents such as bank checks, letters, contracts and many other that require proof of authorship. A person may provide unique information regarding the way she or he converts gesture intentions into spontaneous hand movement. Writing speed, traversed path, pen tilt, pressure applied, all these data are articulated to result in a static figure on signed documents [22]. Either signatures are available through the traditional wet ink method (such as in paper documents), or they are available in scanned form, through optical devices, such as scanners and digital cameras. In both cases, all available data corresponds to static signature images
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