Open AccessJournal Article
Handwritten signature identification using basic concepts of graph theory
TLDR
Previous work in the field of signature and writer identification is presented to show the historical development of the idea and a new promising approach in handwritten signature identification based on some basic concepts of graph theory is defined.Abstract:
Handwritten signature is being used in various applications on daily basis. The problem arises when someone decides to imitate our signature and steal our identity. Therefore, there is a need for adequate protection of signatures and a need for systems that can, with a great degree of certainty, identify who is the signatory. This paper presents previous work in the field of signature and writer identification to show the historical development of the idea and defines a new promising approach in handwritten signature identification based on some basic concepts of graph theory. This principle can be implemented on both on-line handwritten signature recognition systems and off-line handwritten signature recognition systems. Using graph norm for fast classification (filtration of potential users), followed by comparison of each signature graph concepts value against values stored in database, the system reports 94.25% identification accuracy.read more
Citations
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Offline Handwritten Signature Verification Using Deep Neural Networks
TL;DR: Two methods for classifying signatures in an attendance sheet as valid or not are described, one based on Optical Mark Recognition is general but determines only the presence or absence of a signature, and the other uses a multiclass convolutional neural network inspired by the AlexNet architecture.
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Learning non-Gaussian graphical models via Hessian scores and triangular transport
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An efficient approach for dynamic signature recognition
TL;DR: An efficient two-stage online signature recognition approach that depends on the initial analyses of global features using Euclidean distance to quickly discard outlier signatures; then followed by local features analysis using an enhanced DTW algorithm.
References
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Offline signature verification and identification using distance statistics
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Personal identification based on handwriting
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 by taking a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture.
Proceedings ArticleDOI
Biometric personal identification based on handwriting
Zhu Yong,Tieniu Tan,Yunhong Wang +2 more
TL;DR: A new method to identify the writer of Chinese handwritten documents by taking the handwriting as an image containing some special texture, and writer identification is regarded as texture identification, which is a content independent method.
Journal ArticleDOI
Morphological waveform coding for writer identification
TL;DR: Both Bayesian classifiers and neural networks are employed to test the efficiency of the proposed feature and the achieved identification success using a long word exceeds 95%.