Handwritten Signature Veri cation HSV is an automated method of verifying a signature by capturing features about a signature's shape i.e. static features and the characteristics of how the person signs his her name in real time i.e. dynamic features . This system provides a method of handwritten signature recognition and verification using the shapes of the signatures artificial neural network and neural network simulation tool. The shapes of signatures are used to find the features points for features extraction. Then the extracted features are trained by using artificial neural network. A comparison of extracted features is done between the original signature and other relative signatures by using neural simulation toolbox. If the features are matched the system shows that the signature is verified and the person is authorized and unauthorized. Myat Mon Kyaw | San San Nwe | Myint Myint Yee ÄNN Based Handwritten Signature Recognition System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd) ISSN: 2456-6470 Volume-3 | Issue-5 August 2019 URL: https://www.ijtsrd.com/papers/ijtsrd27866.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-processing/27866/ann-based-handwritten-signature-recognition-system/myat-mon-kyaw
%0 Journal Article
%1 noauthororeditor
%A Yee, Myat Mon Kyaw | San San Nwe | Myint Myint
%D 2019
%J International Journal of Trend in Scientific Research and Development
%K Database HSV Processing artificial network neural
%N 5
%P 2094-2097
%R https://doi.org/10.31142/ijtsrd27866
%T ANN Based Handwritten Signature Recognition System
%U https://www.ijtsrd.com/computer-science/data-processing/27866/ann-based-handwritten-signature-recognition-system/myat-mon-kyaw
%V 3
%X Handwritten Signature Veri cation HSV is an automated method of verifying a signature by capturing features about a signature's shape i.e. static features and the characteristics of how the person signs his her name in real time i.e. dynamic features . This system provides a method of handwritten signature recognition and verification using the shapes of the signatures artificial neural network and neural network simulation tool. The shapes of signatures are used to find the features points for features extraction. Then the extracted features are trained by using artificial neural network. A comparison of extracted features is done between the original signature and other relative signatures by using neural simulation toolbox. If the features are matched the system shows that the signature is verified and the person is authorized and unauthorized. Myat Mon Kyaw | San San Nwe | Myint Myint Yee ÄNN Based Handwritten Signature Recognition System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd) ISSN: 2456-6470 Volume-3 | Issue-5 August 2019 URL: https://www.ijtsrd.com/papers/ijtsrd27866.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-processing/27866/ann-based-handwritten-signature-recognition-system/myat-mon-kyaw
@article{noauthororeditor,
abstract = {Handwritten Signature Veri cation HSV is an automated method of verifying a signature by capturing features about a signature's shape i.e. static features and the characteristics of how the person signs his her name in real time i.e. dynamic features . This system provides a method of handwritten signature recognition and verification using the shapes of the signatures artificial neural network and neural network simulation tool. The shapes of signatures are used to find the features points for features extraction. Then the extracted features are trained by using artificial neural network. A comparison of extracted features is done between the original signature and other relative signatures by using neural simulation toolbox. If the features are matched the system shows that the signature is verified and the person is authorized and unauthorized. Myat Mon Kyaw | San San Nwe | Myint Myint Yee "ANN Based Handwritten Signature Recognition System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd) ISSN: 2456-6470 Volume-3 | Issue-5 August 2019 URL: https://www.ijtsrd.com/papers/ijtsrd27866.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-processing/27866/ann-based-handwritten-signature-recognition-system/myat-mon-kyaw
},
added-at = {2019-09-12T14:16:07.000+0200},
author = {Yee, Myat Mon Kyaw | San San Nwe | Myint Myint},
biburl = {https://www.bibsonomy.org/bibtex/29b23484df8082860c3e1590ed0632b0f/ijtsrd},
doi = {https://doi.org/10.31142/ijtsrd27866},
interhash = {db6faea45e6c4f2993445edfcf456999},
intrahash = {9b23484df8082860c3e1590ed0632b0f},
issn = {2456-6470},
journal = {International Journal of Trend in Scientific Research and Development},
keywords = {Database HSV Processing artificial network neural},
language = {English},
month = aug,
number = 5,
pages = {2094-2097},
timestamp = {2019-09-12T14:16:07.000+0200},
title = {ANN Based Handwritten Signature Recognition System
},
url = {https://www.ijtsrd.com/computer-science/data-processing/27866/ann-based-handwritten-signature-recognition-system/myat-mon-kyaw},
volume = 3,
year = 2019
}