Enhancing fingerprint identification using Fuzzy-ANN minutiae matching
‘Based on Minutiae and Neural Networks,’ this paper introduces a robust fingerprint identification system that significantly enhances the accuracy of matching fingerprints, especially those altered due to various reasons such as scars or mutilations. Utilizing a combination of minutiae-based matchin...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Measurement: Sensors |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917425000030 |
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| author | S.P. Singh Dinesh Kumar Nishad Saifullah Khalid |
| author_facet | S.P. Singh Dinesh Kumar Nishad Saifullah Khalid |
| author_sort | S.P. Singh |
| collection | DOAJ |
| description | ‘Based on Minutiae and Neural Networks,’ this paper introduces a robust fingerprint identification system that significantly enhances the accuracy of matching fingerprints, especially those altered due to various reasons such as scars or mutilations. Utilizing a combination of minutiae-based matching and neural network algorithms, the system is designed to overcome the limitations of traditional methods, which often fail under less-than-ideal conditions. The system's core lies in its ability to train an artificial neural network to learn an improved similarity function for minutiae matching. This capability has been extensively validated through a series of rigorous experiments, demonstrating its superiority over existing systems. Implemented in MATLAB, the system performs remarkably on benchmark datasets like FVC2004 DB1 and NIST SD27, achieving state-of-the-art results. This paper not only presents a detailed methodology involving image enhancement, minutiae extraction, and advanced matching techniques but also sets a new standard in fingerprint identification technology, particularly in handling altered fingerprints effectively. |
| format | Article |
| id | doaj-art-efc46a04942a4f90adf6dbca98be7ebe |
| institution | Kabale University |
| issn | 2665-9174 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj-art-efc46a04942a4f90adf6dbca98be7ebe2025-01-26T05:04:54ZengElsevierMeasurement: Sensors2665-91742025-02-0137101809Enhancing fingerprint identification using Fuzzy-ANN minutiae matchingS.P. Singh0Dinesh Kumar Nishad1Saifullah Khalid2Department of Electrical Engineering, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, IndiaDepartment of Electrical Engineering, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, IndiaIBM Multi Activities Co. Ltd, Khartoum, Sudan; Corresponding author. 's‘Based on Minutiae and Neural Networks,’ this paper introduces a robust fingerprint identification system that significantly enhances the accuracy of matching fingerprints, especially those altered due to various reasons such as scars or mutilations. Utilizing a combination of minutiae-based matching and neural network algorithms, the system is designed to overcome the limitations of traditional methods, which often fail under less-than-ideal conditions. The system's core lies in its ability to train an artificial neural network to learn an improved similarity function for minutiae matching. This capability has been extensively validated through a series of rigorous experiments, demonstrating its superiority over existing systems. Implemented in MATLAB, the system performs remarkably on benchmark datasets like FVC2004 DB1 and NIST SD27, achieving state-of-the-art results. This paper not only presents a detailed methodology involving image enhancement, minutiae extraction, and advanced matching techniques but also sets a new standard in fingerprint identification technology, particularly in handling altered fingerprints effectively.http://www.sciencedirect.com/science/article/pii/S2665917425000030MinutiaeFingerprintsANNFUZZYFVC2004 DB1 |
| spellingShingle | S.P. Singh Dinesh Kumar Nishad Saifullah Khalid Enhancing fingerprint identification using Fuzzy-ANN minutiae matching Measurement: Sensors Minutiae Fingerprints ANN FUZZY FVC2004 DB1 |
| title | Enhancing fingerprint identification using Fuzzy-ANN minutiae matching |
| title_full | Enhancing fingerprint identification using Fuzzy-ANN minutiae matching |
| title_fullStr | Enhancing fingerprint identification using Fuzzy-ANN minutiae matching |
| title_full_unstemmed | Enhancing fingerprint identification using Fuzzy-ANN minutiae matching |
| title_short | Enhancing fingerprint identification using Fuzzy-ANN minutiae matching |
| title_sort | enhancing fingerprint identification using fuzzy ann minutiae matching |
| topic | Minutiae Fingerprints ANN FUZZY FVC2004 DB1 |
| url | http://www.sciencedirect.com/science/article/pii/S2665917425000030 |
| work_keys_str_mv | AT spsingh enhancingfingerprintidentificationusingfuzzyannminutiaematching AT dineshkumarnishad enhancingfingerprintidentificationusingfuzzyannminutiaematching AT saifullahkhalid enhancingfingerprintidentificationusingfuzzyannminutiaematching |