Intelligent fingerprint recognition system

The purpose of this project is to design and develop a pattern recognition system with using Artificial Neural Network (ANN) that can recognize the type of image based on the features extracted from the choose image. This system which can fully recognizing the types of the data had been add in the d...

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Bibliographic Details
Main Author: Sy Mohd Syathir, Sy Ali Zainol Abidin
Format: Undergraduates Project Papers
Language:English
Published: 2007
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/77/
http://umpir.ump.edu.my/id/eprint/77/
http://umpir.ump.edu.my/id/eprint/77/1/symohdsyathiree04016ump07thp.pdf
id ump-77
recordtype eprints
spelling ump-772017-02-28T02:45:12Z http://umpir.ump.edu.my/id/eprint/77/ Intelligent fingerprint recognition system Sy Mohd Syathir, Sy Ali Zainol Abidin TK Electrical engineering. Electronics Nuclear engineering The purpose of this project is to design and develop a pattern recognition system with using Artificial Neural Network (ANN) that can recognize the type of image based on the features extracted from the choose image. This system which can fully recognizing the types of the data had been add in the data storage or called as training data. The Graphic User Interface in Neural Network toolbox is used. This is the alternative way to change the common usage of the MATLAB which are use the command insert at command window. From this kind of system, we just need to insert the features data or training data. The recognition done after we insert the test data. The system will recognize whether the output is match with the training data. Then output will produce a kind of graph that describes the feature of the data which is same as the training data. 2007-11 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/77/1/symohdsyathiree04016ump07thp.pdf Sy Mohd Syathir, Sy Ali Zainol Abidin (2007) Intelligent fingerprint recognition system. Faculty of Electrical & Electronic Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:25609&theme=UMP2
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Sy Mohd Syathir, Sy Ali Zainol Abidin
Intelligent fingerprint recognition system
description The purpose of this project is to design and develop a pattern recognition system with using Artificial Neural Network (ANN) that can recognize the type of image based on the features extracted from the choose image. This system which can fully recognizing the types of the data had been add in the data storage or called as training data. The Graphic User Interface in Neural Network toolbox is used. This is the alternative way to change the common usage of the MATLAB which are use the command insert at command window. From this kind of system, we just need to insert the features data or training data. The recognition done after we insert the test data. The system will recognize whether the output is match with the training data. Then output will produce a kind of graph that describes the feature of the data which is same as the training data.
format Undergraduates Project Papers
author Sy Mohd Syathir, Sy Ali Zainol Abidin
author_facet Sy Mohd Syathir, Sy Ali Zainol Abidin
author_sort Sy Mohd Syathir, Sy Ali Zainol Abidin
title Intelligent fingerprint recognition system
title_short Intelligent fingerprint recognition system
title_full Intelligent fingerprint recognition system
title_fullStr Intelligent fingerprint recognition system
title_full_unstemmed Intelligent fingerprint recognition system
title_sort intelligent fingerprint recognition system
publishDate 2007
url http://umpir.ump.edu.my/id/eprint/77/
http://umpir.ump.edu.my/id/eprint/77/
http://umpir.ump.edu.my/id/eprint/77/1/symohdsyathiree04016ump07thp.pdf
first_indexed 2023-09-18T21:51:55Z
last_indexed 2023-09-18T21:51:55Z
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