Leveraging Computer Vision to Biometric Applications (eBook, PDF)

Redaktion: Selwal, Arvind; Lieh, Ouh Eng; Balas, Valentina E.; Chakraborty, Sudeshna; Mann, Mukesh; Sharma, Deepika

• Format: PDF

Produktbeschreibung

Computer vision is an effective solution in a range of real-life applications. With the advent of the machine and deep learning paradigms, this book adopts machine and deep learning algorithms to leverage digital image processing for designing accurate biometrical applications. A must-read for anyone working on computer vision

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 358
• Erscheinungstermin: 7. Oktober 2024
• Englisch
• ISBN-13: 9781040120569
• Artikelnr.: 72284194

Autorenporträt

Arvind Selwal has been an as Assistant Professor in the Department of Computer Science and Information Technology, Central University of Jammu, Jammu & Kashmir, India since 2013. He holds a BTech (CSE), MTech (CSE), and PhD (CSE) degrees as well as being qualified for UGC-NET (Assistant Professor) three times and GATE four times. He has more than 12 years of experience in teaching and research. His research interests include biometric security, cyber security, pattern recognition, digital image processing, lightweight cryptography, machine learning, and soft computing. He has contributed more than 72 research articles in various reputed international journals/conference proceedings/ book chapters that are indexed in databases such as Web of Science, Scopus, and DBLP. He has served as a member of the technical program committee (TPC) at many reputed international conferences. He also serves as a reviewer of several international journals that are published by reputed publishers such as Springer, Elsevier, and IEEE. He has supervised 1 PhD and 21 MTech students and currently supervising 4 PhD scholars and 5 MTech students. He has authored a book titled Fundamentals of Automata Theory and Computation and co-editor of a book titled Data Science and Innovations for Intelligent Systems Computational Excellence and Society 5.0 by Taylor & Francis. Besides being a resource person in many reputed workshops/FDPS, he is also a keen learner and enhances his skills by continuously participating in reputed international conferences/workshops. He is an active member of the Computer Society of India (CSI). Presently, he is undertaking two research projects as PI/Co-PI on the topic of computational security from funding agencies like DRDO, Ministry of Defence (Government of India), New Delhi, India. Deepika Sharma is an active researcher in the Department of Computer Science and Information Technology, Central University of Jammu, India, in the field of Biometrics Security. She has completed her PhD from the Central University of Jammu, India, in the field of Biometrics Security. She received her master's degree in computer applications (MCA) from the Department of Computer Science and Information Technology, Central University of Jammu, Jammu and Kashmir, India, in the year 2017. Prior to that, she completed her Bachelor of Computer Applications (BCA) from the University of Jammu in 2014. Her research interests include biometric security, computer vision pattern recognition, machine learning, and deep learning. She has contributed more than 21 research articles in reputed international journals that are indexed in SCI/ Scopus databases and conferences. She has cleared UGC-NET exam and SET (J&K) exam once. She filed an Indian patent in 2022. Mukesh Mann is an Assistant Professor, Indian Institute of Information Technology (IIIT), Sonipat, India. He earned his PhD (Computer Science and Engineering) from Gautam Budha University. He earned his MTech degree from Gautam Budha University in Computer Science and Engineering. He has completed his BTech from Kurukshetra University in Computer Science and Engineering. His research interests include information security, computer vision blockchain, machine learning, and deep learning. He has contributed more than 30 research articles in reputed international journals that are indexed in SCI/Scopus databases and reputed national/international conferences. He is a recipient of the Direct Senior Research Fellow award in Computer Science and Engineering by the Council of Scientific and Industrial Research, Govt. of India. He was also awarded the Junior Research Fellowship award and the Senior Research Fellow award by the University Grant Commission (UGC), Govt. of India, for research and development. Sudeshna Chakraborty is a research group leader and professor at the School of Computing Science & Engineering, Galgotias University, Greater Noida, India. She is an experienced academician in the field of Computer Science. She has a PhD in Computer Science & Engineering in Semantic Web Engineering, has versatile experience in industry and academics with the recipient of best IT faculty at INC Hyderabad, and was also a distinguished Academician in 2020-2021 at Sharda University. Dr. Chakraborty has earned several other awards for the best paper presented, keynote speaker, reviewer's committee, session chairs, highest cited author, and many others. She was the recipient of the Outstanding Academician Award in 2020 and Research Excellence Award and the Academician's Award by the Institute of Scholars in 2021 and Nikhil Bhartiya Parishad Shiksha Parishad in 2022. She chaired the IEEE conference in Paris ICACCE in 2018 and the Springer conference in Spain. She was the recipient of the Best Speaker Award on Roles & Trends of Engineers on Engineering Day by the Institution of Engineers of India. She has been instrumental in various industrial interfacing for academic and research at her previous assignments at various organizations (Manav Rachna University, Mumbai University, Lingaya's, and others). She has 75+ publications in Scopus Indexed/SCI/high-impact journals and international conferences, 18 patents published, and 4 granted. Dr. Chakraborty is guiding various PhD students at the university. She has successfully guided several PG and UG students; additionally, she has contributed to various prestigious accreditations like NAAC, NBA, QAA, WASC, UGC, IAU, IET, and others. Valentina E. Balas is a Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, "Aurel Vlaicu" University of Arad, Romania. She holds a PhD Cum Laude in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is the author of more than 400 research papers. Her research interests are in intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, and modeling and simulation. She is the Editor-in-Chief to IJAIP and IJCSysE journals in Inderscience, a member of the editorial board of several national and international journals, and evaluator expert for national and international projects and PhD thesis. Dr. Balas is the Director of the Intelligent Systems Research Centre and Director of the Department of International Relations at Aurel Vlaicu University of Arad. During the interval 2021-2022, she was a member of the IEEE European Public Policy Committee Working Group on ICT. From May 2023, Dr. Balas is an associate member of the Romanian Academy of Scientists. She is the recipient of the "Tudor Tanasescu" Prize from the Romanian Academy for contributions to the field of soft computing methods (2019), "Stefan Odobleja" Prize from the Romanian Academy of Scientists (2023), and Diploma - Section Information Technology from The General Association of the Engineers in Romania (AGIR) 2023. Ouh Eng Lieh earned his PhD in Computer Science (Software Engineering) from the National University of Singapore. He is currently involved in undergraduate education as Assistant Professor of Information Systems (Education) at the School of Computing and Information Systems, Singapore Management University. His research interests are in software reuse and education pedagogy. He served as a member of the program committee of several conferences and has numerous publications in the software engineering, computer science, and information systems education conferences. He is involved in several largescale information technology industry projects for a decade before joining academia as an educator. His research areas are software

Inhaltsangabe

1. An overview of biometrics and its applications. 2. Leveraging computer
vision to biometrics. 3. Demystifying deep learning for fingerprint
recognition. 4. Computer vision for face recognition. 5. Robust iris-based
systems via deep models.6. Security and privacy issues in biometric
system.7. Deep learning-enabled solutions to countermeasure biometric
attacks. 8. Biometric applications in surveillance. 9. Computer
vision-assisted anti-spoofing for fingerprint systems. 10. Iris
anti-spoofing through vision-based approaches. 11. Deep learning-based
countermeasures for face spoof attacks. 12. Deep learning-inspired
biometrics for video analysis. 13. Digital forensics and its applications.
14. Biometric-based solutions for government policies. 15. Covid-19
challenges for biometrics. 16. Computer vision for biometric applications.
Issues and solutions.