Proceedings ArticleDOI
Writer identification using edge-based directional features
M. Bulacu,Lambert Schomaker,Louis Vuurpijl +2 more
- Vol. 3, pp 937-941
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TLDR
The joint probability distribution of theangle combination of two "hinged" edge fragments outperforms all other individual features and may improve the performance of edge-based directional probability distributions in writer identification procedures.Abstract:
This paper evaluates the performance of edge-based directionalprobability distributions as features in writer identificationin comparison to a number of non-angular features.It is noted that the joint probability distribution of theangle combination of two "hinged" edge fragments outperformsall other individual features. Combining features mayimprove the performance. Limitations of the method pertainto the amount of handwritten material needed in orderto obtain reliable distribution estimates. The global featurestreated in this study are sensitive to major style variation(upper- vs lower case), slant, and forged styles, whichnecessitates the use of other features in realistic forensicwriter identification procedures.read more
Citations
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Journal ArticleDOI
Text-Independent Writer Identification and Verification Using Textural and Allographic Features
M. Bulacu,Lambert Schomaker +1 more
TL;DR: New and very effective techniques for automatic writer identification and verification that use probability distribution functions (PDFs) extracted from the handwriting images to characterize writer individuality are developed.
Journal ArticleDOI
Automatic writer identification using connected-component contours and edge-based features of uppercase Western script
Lambert Schomaker,M. Bulacu +1 more
TL;DR: The proposed automatic approach bridges the gap between image-statistics approaches on one end and manually measured allograph features of individual characters on the other end, and revealed a high-sensitivity of the CO/sup 3/ PDF for identifying individual writers on the basis of a single sentence of uppercase characters.
Journal ArticleDOI
Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features
Imran Siddiqi,Nicole Vincent +1 more
TL;DR: An effective method for automatic writer recognition from unconstrained handwritten text images based on the presence of redundant patterns in the writing and its visual attributes is proposed, which exhibits promising results on writer identification and verification.
Journal ArticleDOI
Texture-based descriptors for writer identification and verification
TL;DR: Through a series of comprehensive experiments, this work shows that both LBP- and LPQ-based classifiers are able to surpass previous results reported in the literature for the verification problem by about 5 percentage points, and the proposed approach using LPQ features is able to achieve accuracies of 96.7% and 99.2% on the BFL and IAM and databases respectively.
Journal ArticleDOI
Using codebooks of fragmented connected-component contours in forensic and historic writer identification
TL;DR: New algorithms for forensic or historical writer identification, using the contours of fragmented connected-components in free-style handwriting, are described, showing usable classification rates within a non-critical range of Kohonen map dimensions.
References
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Journal ArticleDOI
An evaluation of motor models of handwriting
Réjean Plamondon,F.J. Maarse +1 more
TL;DR: Results show that velocity-controlled models produce the best outputs, with no significant difference between second- and third-order systems, and are of interest for a number of applications, from pattern recognition to handwriting education.
Journal ArticleDOI
Produced and perceived writing slant: difference between up and down strokes.
TL;DR: The most important conclusion is that horizontal movement is not constant, but dependent on the strokes being made in handwriting, which appears to be bigger during up strokes than during down strokes.
Proceedings ArticleDOI
A set of handwriting families: style recognition
TL;DR: Based on an analysis of 980 different handwritten amounts, it is shown that these measures define a variability space of non-uniform density that allows to regroup handwriting styles into a small number of specific families.
Proceedings ArticleDOI
Writer Identification from Non-uniformly Skewed Handwriting Images
TL;DR: This paper attempts to eliminate the assumption that the written text is fixed by presenting a novel algorithm for automatic text-independent writer identification from non-uniformly skewed handwriting images by taking a global approach based on texture analysis.
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Text-Independent Writer Identification and Verification Using Textural and Allographic Features
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