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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | CNN BASED FINGERPRINT EXTRACTION AND RECOGNITION |
| Authors Name: | Kareem Badhusha , Mohammed Faruk , Mohammed Arif , Saravanan Elumala , Dr. T. Kiruba Devi |
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IJNRD_189830
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| Published Paper Id: | IJNRD2304044 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | Contactless fingerprint authentication is becoming increasingly popular due to its potential to offer both improved hygiene and increased accuracy in personal authentication. Although non-contact 2D imaging has its benefits, it typically demands a significant level of user participation and often leads to incomplete 2D fingerprint capture. To address this issue, we approached to Convolutional Neural Network framework for identifying fingerprint images using a database in our project. Our framework first trains a CNN (Convolutional Neural Network) using fingerprint feature points and specific ridge map regions. More accurate and better results were obtained with several popular deep learning techniques presented in this paper. In this study demonstrate the effectiveness of the proposed approach and show significant improvements in fingerprint recognition methods. The proposed work also helps curb fingerprint spoofing, thereby improving security. The CNN (Convolutional Neural Network) based fingerprint extraction and recognition can be used for contactless provides higher level of hygiene more often required solution to tackle security threats proposed in the year 2019 and after all due to occurrence and world wide spread of the Covid-19 pandemic which made necessary restriction of being in physical contact with other person or commonly touched objects. |
| Keywords: | Convolutional Neural Network, Fully Connected, Cellular Neural Network, Artificial Intelligence, Computer Vision, Magnetic Resonance Imaging. |
| Cite Article: | "CNN BASED FINGERPRINT EXTRACTION AND RECOGNITION", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.a370-a374, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304044.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2304044 Registration ID: 189830 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: a370-a374 Country: Chennai, Tamil Nadu, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304044 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304044 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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