Open AccessHEURISTIC TECHNIQUES FOR HANDWRITTEN SIGNATURE CLASSIFICATION
Author(s) -
Marcin Adamski,
Khalid Saeed
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.5.2.401
Subject(s) - dynamic time warping , signature (topology) , pattern recognition (psychology) , computer science , tracing , boundary (topology) , feature (linguistics) , artificial intelligence , feature vector , polar coordinate system , sliding window protocol , image (mathematics) , heuristic , algorithm , feature extraction , window (computing) , mathematics , geometry , mathematical analysis , linguistics , philosophy , operating system
New theoretical and experimental techniques for offline classification of handwritten signatures are introduced in this paper. The proposed algorithms are mainly based on boundary tracing technique for extracting characteristic features. Outer and inner boundaries of the signature image are treated separately. The upper and lower parts of the boundaries are extracted to form two sequences of points. Three algorithms for calculating feature vectors are applied based on y coordinate, distances between consecutive points and from polar coordinates system. Experiments on classification of the resulted vectors were carried out by means of Dynamic Time Warping algorithm using window and slope constraints. A brief comparison between the authors' work and other known signature techniques is also discussed in the paper.