A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition
In this modern age of electronic interactions, more secure methods are required to protect vital information. Passwords are indeed a prominent and secure method, but they are subject to being forgotten, especially if they are long and complex. A more efficient way is the use of human fingerprints,...
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University of Baghdad, College of Science for Women
2024-11-01
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| Series: | مجلة بغداد للعلوم |
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| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8777 |
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| author | Ekhlas Falih Naser Enas Tariq Khudair Eman Shakir Mahmood Abeer Tariq Maolood |
| author_facet | Ekhlas Falih Naser Enas Tariq Khudair Eman Shakir Mahmood Abeer Tariq Maolood |
| author_sort | Ekhlas Falih Naser |
| collection | DOAJ |
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In this modern age of electronic interactions, more secure methods are required to protect vital information. Passwords are indeed a prominent and secure method, but they are subject to being forgotten, especially if they are long and complex. A more efficient way is the use of human fingerprints, which are unique to each person. No two people would have the same fingerprint even if they were a twin, which makes it a very secure method that cannot be duplicated or forgotten. This research aims to compare seven moments and backpropagation for more accurate fingerprint recognition within video frames. The first method is the "seven moments," and the second method is the Backpropagation Neural Network (BPNN), both applied to the interest points that are extracted from each frame. For extracting the interest points from each one of the frames, Smallest Univalue Segment Assimilating Nucleus (SUSAN), a corner detector, was employed. Multiple examples of video frames were used in comparison, and the findings demonstrated that the BPNN approach was more accurate even when the fingerprint had a significant amount of corrupted data or unclear image pixels.
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| format | Article |
| id | doaj-art-2b88a9600a184e4b959f223a55a4d4b5 |
| institution | DOAJ |
| issn | 2078-8665 2411-7986 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | University of Baghdad, College of Science for Women |
| record_format | Article |
| series | مجلة بغداد للعلوم |
| spelling | doaj-art-2b88a9600a184e4b959f223a55a4d4b52025-08-20T03:15:39ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862024-11-01211110.21123/bsj.2024.8777A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames RecognitionEkhlas Falih Naser 0https://orcid.org/0000-0002-6543-7751Enas Tariq Khudair1Eman Shakir Mahmood2Abeer Tariq Maolood 3Department of Computer Sciences, University of Technology, Baghdad, Iraq Department of Computer Sciences, University of Technology, Baghdad, Iraq Department of Computer Sciences, University of Technology, Baghdad, Iraq.Department of Computer Sciences, University of Technology, Baghdad, Iraq. In this modern age of electronic interactions, more secure methods are required to protect vital information. Passwords are indeed a prominent and secure method, but they are subject to being forgotten, especially if they are long and complex. A more efficient way is the use of human fingerprints, which are unique to each person. No two people would have the same fingerprint even if they were a twin, which makes it a very secure method that cannot be duplicated or forgotten. This research aims to compare seven moments and backpropagation for more accurate fingerprint recognition within video frames. The first method is the "seven moments," and the second method is the Backpropagation Neural Network (BPNN), both applied to the interest points that are extracted from each frame. For extracting the interest points from each one of the frames, Smallest Univalue Segment Assimilating Nucleus (SUSAN), a corner detector, was employed. Multiple examples of video frames were used in comparison, and the findings demonstrated that the BPNN approach was more accurate even when the fingerprint had a significant amount of corrupted data or unclear image pixels. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8777BackPropagation, Fingerprint, Recognition, Seven Moments, SUSAN Detector. |
| spellingShingle | Ekhlas Falih Naser Enas Tariq Khudair Eman Shakir Mahmood Abeer Tariq Maolood A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition مجلة بغداد للعلوم BackPropagation, Fingerprint, Recognition, Seven Moments, SUSAN Detector. |
| title | A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition |
| title_full | A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition |
| title_fullStr | A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition |
| title_full_unstemmed | A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition |
| title_short | A Comparison between Backpropagation Neural Network and Seven Moments for More Accurate Fingerprint Video Frames Recognition |
| title_sort | comparison between backpropagation neural network and seven moments for more accurate fingerprint video frames recognition |
| topic | BackPropagation, Fingerprint, Recognition, Seven Moments, SUSAN Detector. |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8777 |
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