Offline signature authenticity verification through unambiguously connected skeleton segments
Jugurta Montalv\~ao, Luiz Miranda, J\^anio Canuto

TL;DR
This paper introduces a novel offline signature verification method using skeleton segmentation into unambiguous segments, encoded compactly, and compares its effectiveness to other approaches and human performance.
Contribution
It proposes a new skeleton segmentation-based approach for signature verification, emphasizing compact encoding and Euclidean distance comparison, achieving results close to human accuracy.
Findings
Method performs comparably to human verification.
Simple equal-weight strategy yields best results.
Outperforms other automated approaches on MCYT-100.
Abstract
A method for offline signature verification is presented in this paper. It is based on the segmentation of the signature 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsDynamic Time Warping
