Offline Signature Verification via Structural Methods: Graph Edit Distance and Inkball Models

For handwritten signature verification, signature images are typically represented with fixed-sized feature vectors capturing local and global properties of the handwriting. Graphbased representations offer a promising alternative, as they are flexible in size and model the global structure of the handwriting. However, they are only rarely used for signature verification, which may be due to the high computational complexity involved when matching two graphs. In this paper, we take a closer look at two recently presented structural methods for handwriting analysis, for which efficient matching methods are available: keypoint graphs with approximate graph edit distance and inkball models. Inkball models, in particular, have never been used for signature verification before. We investigate both approaches individually and propose a combined verification system, which demonstrates an excellent performance on the MCYT and GPDS benchmark data sets when compared with the state of the art

Graph-Based Offline Signature Verification

Graphs provide a powerful representation formalism that offers great promise to benefit tasks like handwritten signature verification. While most state-of-the-art approaches to signature verification rely on fixed-size representations, graphs are flexible in size and allow modeling local features as well as the global structure of the handwriting. In this article, we present two recent graph-based approaches to offline signature verification: keypoint graphs with approximated graph edit distance and inkball models. We provide a comprehensive description of the methods, propose improvements both in terms of computational time and accuracy, and report experimental results for four benchmark datasets. The proposed methods achieve top results for several benchmarks, highlighting the potential of graph-based signature verification

Definition and evaluation of a family of shape factors for off-line signature verification

In a real situation, the choice of the best representation for the implementation of a signature verification system able to cope with all types of handwriting is a very difficult task. This study is original in that the design of the integrated classifiers is based on a large number of individual classifiers (or signature representations) in an attempt to overcome in some way the need for feature selection. In fact, the cooperation of a large number of classifiers is justified only if the cost of individual classifiers is low enough . This is why the extended shadow code (ESC) used as a class of shape factors tailor-made for the signature verification problem seems a good choice for the design of integrated classifiers E(x) .Nous proposons dans cet article une voie à suivre pour tenter d'apporter une solution au problème complexe qu'est la définition d'un facteur de forme adapté au problème de la vérification automatique des signatures manuscrites. Le codage de la signature obtenu de la projection locale du tracé sur les segments d'un motif M(γ) est un compromis entre les approches globales où la silhouette de la signature est considérée comme un tout, et les approches locales où des mesures sont effectuées sur des portions spécifiques du tracé. Inspiré de ces deux familles d'approches, l'ESC est en fait une approche mixte qui permet d'effectuer des mesures locales sur la forme sans la segmenter en primitives élémentaires, une tâche très difficile en pratique. Ce travail porte principalement sur l'étude de l'influence de la résolution des motifs utilisés pour le codage de la signature (par la projection locale du tracé), et sur la définition d'un système de type multi-classifieurs pour tenter de rendre plus robuste la performance des systèmes de vérification de signatures

Multi-feature approach for writer-independent offline signature verification

Some of the fundamental problems facing handwritten signature verification are the large number of users, the large number of features, the limited number of reference signatures for training, the high intra-personal variability of the signatures and the unavailability of forgeries as counterexamples. This research first presents a survey of offline signature verification techniques, focusing on the feature extraction and verification strategies. The goal is to present the most important advances, as well as the current challenges in this field. Of particular interest are the techniques that allow for designing a signature verification system based on a limited amount of data. Next is presented a novel offline signature verification system based on multiple feature extraction techniques, dichotomy transformation and boosting feature selection. Using multiple feature extraction techniques increases the diversity of information extracted from the signature, thereby producing features that mitigate intra-personal variability, while dichotomy transformation ensures writer-independent classification, thus relieving the verification system from the burden of a large number of users. Finally, using boosting feature selection allows for a low cost writer-independent verification system that selects features while learning. As such, the proposed system provides a practical framework to explore and learn from problems with numerous potential features. Comparison of simulation results from systems found in literature confirms the viability of the proposed system, even when only a single reference signature is available. The proposed system provides an efficient solution to a wide range problems (eg. biometric authentication) with limited training samples, new training samples emerging during operations, numerous classes, and few or no counterexamples

Proposition d'une méthode d'inférence de la séquence dans l'image d'une signature manuscrite

La vérification de signatures -- L'inférence de la séquence -- Proposition de recherche -- Traitement de l'information statique -- Description générale -- Prétraitement de l'image -- Formation des zones extremums -- Formation des zones de discontinuité -- Formation du graphe de relations -- Traitement de l'information dynamique -- Interpolation de la trajectoire -- Formation des zones caractéristiques -- Graphe de représentation -- Mise en correspondance des graphes -- Développement du graphe de relations -- Mise en correspondance par relaxation -- Mise en correspondance par croissance consistance -- Squellettisation de l'image -- Définition du squelette -- Squelettisation de signaux manuscrits -- Squelettisation de la signature manuscrite -- Évaluations des performances -- Composition et acquisition de la banque de données -- Métriques définies pour l'évaluation des performances -- Étapes d'évaluation des performances -- Évaluation de l'efficacité -- Évaluation de la capacité de détection des faux aléatoires -- Rappel des objectifs et travail accompli -- Contribution originale -- Limites et contraintes -- Nouvelles voies de recherche