User identification system for inked fingerprint pattern based on central moments
The use of the fingerprint recognition has been and remains very important in many security applications and licensing systems. Fingerprint recognition is required in many areas such as licensing access to networks, corporate computers and organizations. In this paper, the system of fingerprint reco...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32758/1/User%20identification%20system%20for%20inked%20fingerprint%20pattern%20based%20on%20central%20moments.pdf http://umpir.ump.edu.my/id/eprint/32758/ http://doi.org/10.11591/ijeecs.v24.i2.pp1149-1160 http://doi.org/10.11591/ijeecs.v24.i2.pp1149-1160 |
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| Summary: | The use of the fingerprint recognition has been and remains very important in many security applications and licensing systems. Fingerprint recognition is required in many areas such as licensing access to networks, corporate computers and organizations. In this paper, the system of fingerprint recognition that can be used in several cases of fingerprint such as being rounded at an angle by a randomly inked fingerprint on paper. So, fingerprint image is tooked at a different angle in order to identify the owner of the ink fingerprint. This method involves two working levels. The first one, the fingerprint pattern's shape features are calculated based on the central moments of each image being listed on a regular basis with three states rotation. Each image is rotated at a specified angle. In the second level, the fingerprint holder entered is identified using the previously extracted shape features and compared to the three local databases content of three rotation states. When applied the method for several persons by taken their inked fingerprint on the paper, the accuracy of the system in identifying the owner of the fingerprint after rotation states were close to 83.71. |
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