Classification of thumbprint using Artificial Neural Network (ANN)
This paper presents the classification of thumbprint using Artificial Neural Network (ANN). The ANN technique is conducted in order to improve the minutia extraction techniques. The classification of thumbprint is used in order to match the person's identification and train the data by using AN...
Published in: | Proceedings - 2011 IEEE International Conference on System Engineering and Technology, ICSET 2011 |
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2-s2.0-80052842979 Naim N.F.; Yassin A.I.M.; Zakaria N.B.; Wahab N.A. Classification of thumbprint using Artificial Neural Network (ANN) 2011 Proceedings - 2011 IEEE International Conference on System Engineering and Technology, ICSET 2011 10.1109/ICSEngT.2011.5993456 https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052842979&doi=10.1109%2fICSEngT.2011.5993456&partnerID=40&md5=6bba3b79056c460867a010870c2fea36 This paper presents the classification of thumbprint using Artificial Neural Network (ANN). The ANN technique is conducted in order to improve the minutia extraction techniques. The classification of thumbprint is used in order to match the person's identification and train the data by using ANN. The data of thumbprint is taken from five different people. For each person, 30 thumbprint data is taken. All the data will be the input for artificial neural network for learning purposes. All the data will be adjusted using Corel. Then by using Matlab software, the data is trained and tested according to the artificial neural network program. This is to ensure that the output is matched with the input data. The result will be shown in the graph to identify whether the system is sufficient for training the thumbprint data. It can also be used for person identification. Therefore, the result shows that the system is accurate in training the data. © 2011 IEEE. English Conference paper |
author |
Naim N.F.; Yassin A.I.M.; Zakaria N.B.; Wahab N.A. |
spellingShingle |
Naim N.F.; Yassin A.I.M.; Zakaria N.B.; Wahab N.A. Classification of thumbprint using Artificial Neural Network (ANN) |
author_facet |
Naim N.F.; Yassin A.I.M.; Zakaria N.B.; Wahab N.A. |
author_sort |
Naim N.F.; Yassin A.I.M.; Zakaria N.B.; Wahab N.A. |
title |
Classification of thumbprint using Artificial Neural Network (ANN) |
title_short |
Classification of thumbprint using Artificial Neural Network (ANN) |
title_full |
Classification of thumbprint using Artificial Neural Network (ANN) |
title_fullStr |
Classification of thumbprint using Artificial Neural Network (ANN) |
title_full_unstemmed |
Classification of thumbprint using Artificial Neural Network (ANN) |
title_sort |
Classification of thumbprint using Artificial Neural Network (ANN) |
publishDate |
2011 |
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Proceedings - 2011 IEEE International Conference on System Engineering and Technology, ICSET 2011 |
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10.1109/ICSEngT.2011.5993456 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052842979&doi=10.1109%2fICSEngT.2011.5993456&partnerID=40&md5=6bba3b79056c460867a010870c2fea36 |
description |
This paper presents the classification of thumbprint using Artificial Neural Network (ANN). The ANN technique is conducted in order to improve the minutia extraction techniques. The classification of thumbprint is used in order to match the person's identification and train the data by using ANN. The data of thumbprint is taken from five different people. For each person, 30 thumbprint data is taken. All the data will be the input for artificial neural network for learning purposes. All the data will be adjusted using Corel. Then by using Matlab software, the data is trained and tested according to the artificial neural network program. This is to ensure that the output is matched with the input data. The result will be shown in the graph to identify whether the system is sufficient for training the thumbprint data. It can also be used for person identification. Therefore, the result shows that the system is accurate in training the data. © 2011 IEEE. |
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English |
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Conference paper |
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Scopus |
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1809677914136903680 |