Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/341262
Title: | User authentication using multimodal biometric techniques |
Researcher: | kumar Surender |
Guide(s): | Bathla R.K, Manro Rajan |
Keywords: | Computer Science engineering Computer Science engineering Engineering and Technology |
University: | Desh Bhagat University |
Completed Date: | 2020 |
Abstract: | newline newline ABSTRACT newlineUser Authentication using Multimodal Biometric Techniques newlineBiometric system used for authentication provides high scale of security for different variety of applications as compared to conventional authentication mechanism (like pin, passwords etc.).Biometric system can apply to different field of our society in different application. These applications includes authentication for personal computer, attendance system in different organization, banking system and transactions, personal data protection, securing building access and airport security etc. The biometric system uses the physical and behavioral biometric traits of person for identification and verification. The thesis defines impact of biometric system in our todayand#8223;s life. Presently the recognition of user, single trait of biometric is used but it do not provide better authentication for highly secured application. To overcome these problems the Multimodal biometric systems is used. Multimodal biometric system includes physical and behavioral traits for user authentication for example, finger print and face, fingerprint and signature etc. Further, soft biometric traits are also used which includes skin color, age, height, hair color, eye color, gender etc. The soft biometric also have limitation i.e., lack of permanency and distinct behavior, while it can be used to improve the performance of biometric system with other traits. The thesis work is divided into three parts. In the first part a framework/algorithms designed in multimodal biometric system by fusing face and fingerprint biometric trait. newlineIn second part of the work algorithm is designed using iris and face traits with soft biometrics in the multimodal biometric system. Further, in the third part of the work the biometric performance is improved by using soft biometric traits and also liveness detection in face recognition is used and a comparison is made between existing techniques and the present work. newlineThe work present in the thesis improves the authentication, security and newlinepe |
Pagination: | |
URI: | http://hdl.handle.net/10603/341262 |
Appears in Departments: | Department of Engineering and Technology |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 16.73 MB | Adobe PDF | View/Open |
abstract.pdf | 101.6 kB | Adobe PDF | View/Open | |
acknowledgment.pdf | 11.13 kB | Adobe PDF | View/Open | |
bibliography.pdf | 385.47 kB | Adobe PDF | View/Open | |
certificate.pdf | 88.34 kB | Adobe PDF | View/Open | |
chapter 1.pdf | 1.28 MB | Adobe PDF | View/Open | |
chapter 2.pdf | 297.11 kB | Adobe PDF | View/Open | |
chapter 4.pdf | 545.82 kB | Adobe PDF | View/Open | |
chapter 5.pdf | 707.25 kB | Adobe PDF | View/Open | |
chapter 6.pdf | 400.13 kB | Adobe PDF | View/Open | |
chapter 7.pdf | 248.04 kB | Adobe PDF | View/Open | |
declaration.pdf | 87.26 kB | Adobe PDF | View/Open | |
front page.pdf | 10.47 kB | Adobe PDF | View/Open | |
list of abbreviations.pdf | 21.58 kB | Adobe PDF | View/Open | |
list of contents.pdf | 101.68 kB | Adobe PDF | View/Open | |
list of figures.pdf | 64.73 kB | Adobe PDF | View/Open | |
list of tables.pdf | 22.19 kB | Adobe PDF | View/Open | |
paper presented.pdf | 16.73 MB | Adobe PDF | View/Open | |
thesis outline.pdf | 7.76 kB | Adobe PDF | View/Open |
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