RETRACTED ARTICLE: Fingerprint classification system using CNN
Most solitary finger impression check and acknowledgment frameworks / methods are based on the minutiae feature points. Feature Extraction is a fundamental advance in solitary finger impression based acknowledgment frameworks. In this paper, a CNN based finger impression affirmation strategy is prop...
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| Veröffentlicht in: | Multimedia tools and applications 2022-07, Vol.81 (17), p.24515-24527 |
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| container_title | Multimedia tools and applications |
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| creator | Nahar, Prateek Chaudhari, N. S. Tanwani, S. K. |
| description | Most solitary finger impression check and acknowledgment frameworks / methods are based on the minutiae feature points. Feature Extraction is a fundamental advance in solitary finger impression based acknowledgment frameworks. In this paper, a CNN based finger impression affirmation strategy is proposed without preprocessing an image. The framework fuses two phases include extraction and coordinating. Feature elicitation is realized by different filters with different parameter set; matching juncture relates extracted features and creates a corresponding score. Recognition attainment of the preferred system has been tested by utilizingFVC2004 database. The inference is very favoring for implementing a CNN based self-regulating fingerprint recognition system. Our method achieves an overall rate of 99.1% of accurately classified samples. |
| doi_str_mv | 10.1007/s11042-022-12294-4 |
| format | Article |
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The inference is very favoring for implementing a CNN based self-regulating fingerprint recognition system. 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| subjects | Biometric recognition systems Biometrics Classification Computer Communication Networks Computer Science Data Structures and Information Theory Deep learning Feature extraction Fingerprint verification Multimedia Multimedia Information Systems Neural networks Special Purpose and Application-Based Systems |
| title | RETRACTED ARTICLE: Fingerprint classification system using CNN |
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