Fusion based Multimodal Biometric cryptosystem

Dandawate, Yogesh H.; Inamdar, Sajeeda R.

doi:10.1109/iic.2015.7150984

Cited by 16 publications

(4 citation statements)

References 11 publications

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“…Chaudhary, and Sheetal, et al [10] FpVTE 2003 was analysis to performance and calculated the efficiency of proposed method, fingerprint verification and identification systems. Its summary and analysis report Meva et al, [11] and NIST Biometric and Evaluation and Development paper by Hassan, Norsalina, and Dzati Athiar Ramli et al, [12], Dandawate, and Yogesh H et al [13] and W. Yang, integrated information presented by two fingers at the match score level by probability proportion calculated nonparametric statistical estimates. It was found that multiple fingers improve the verification performance by 4%.…”

Section: \ Fig1 Block Diagram For Multimodal Fusion Methodsmentioning

confidence: 99%

Robust Iris and Fingerprint Biometric Fusion in Multimodal Feature Template Matching

Vijayakumar.¹,

K²

2019

IJRTE

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Abstract: A fusion scheme in multimodal biometric system is proposed in the name of Multimodal Feature Template Matching (MTM) system derived from the two picture fused values of average point and weighted assessment point. The main objective of MTM algorithm is to design the average point fusion and weighted average point by fusion of Iris and fingerprint features. The MTM algorithm is assigned with avgweights based on their verification accuracy. A hybrid approach of combining biometric image level information id presented. The raw information is merged at image level. This integration addressed, provides a small template and resilience to attacks. However it does not improve the recognition performance, but the performances is also less combination to its unimodal counterpart. Confidence level integration of compatible features of two different uncorrelated biometric traits fingerprint and iris provides sustainable improvement in performance accuracy compared to other integration methods as well as best unimodal system. Fingerprint and iris integrationapproaches presented in this proposed are more robust and reliable.

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Section: \ Fig1 Block Diagram For Multimodal Fusion Methodsmentioning

confidence: 99%

Robust Iris and Fingerprint Biometric Fusion in Multimodal Feature Template Matching

Vijayakumar.¹,

K²

2019

IJRTE

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“…The time of transaction is only 10 seconds and since encryption is performed it reduces power consumption but the issues in this system is that ATM pins can be easily guessed, stolen or misused and fingerprints can also be forged. Yogesh.H.Dandawate et.al., [4] proposes a system which captures two biometric traits-Fingerprint and Palm Vein. The first process involves feature extraction which includes fingerprint extraction using smoothing algorithm and palm vein extraction using curvelet transform.…”

Section: IImentioning

confidence: 99%

Survey on Enhanced Cardless Transaction using Biometric ATMs

Geetha¹

2020

IJRASET

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Automated Teller Machines (ATM) are widely used now-a-days by people. These are electronic machines which are operated by customers to deposit or withdraw cash from banks. ATM provides services round the clock and is installed at convenient places including both onsite and offsite. In traditional ATM system card and pin numbers are used for authentication, where security plays a big concern such as losing cards, stolen pin numbers. In order to minimize these issues this paper discusses a system where ATM cards and pins are replaced by biometrics thus the combination of biometrics will be difficult to break the security. This process provides authentication for withdrawal of cash from ATM when the user's fingerprint and face recognition matches the collected datasets. In this system Raspberry pi microcontroller is used in the controlling part. It performs the search operation in the Database and sends necessary information to a display device. Open CV libraries are used for the method of recognition verification and identification of face images. Moreover to improve the efficiency of the system Haar Cascade is used.

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“…The matrix arrangement of LED's is placed below and the camera is mounted on a wooden stand above at height of 15 cm (Dandawate and Inamdar, 2015). A glass cover is placed over the LED's to provide a base for the placement of hand of the subject.…”

Section: Actual Systemmentioning

confidence: 99%

Multimodal biometric cryptosystem based on fusion of wavelet and curvelet features in robust security application

Inamdar¹,

Dandawate²

2016

IJBM

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The authentication system used at the automated teller machines (ATM) is a unique personal identification number (PIN). This PIN can be easily tapped and misused. In this paper we propose a method in which the PIN is replaced by the biometrics of the individual to have a more secure transaction. A complete hardware system is designed to capture the biometric traits such as face, fingerprint and palm vein. The captured images are pre-processed and then features are extracted which are then fused at feature level. Cryptography is applied on the fused feature vector. Matching is performed using Euclidean distance at the server end. Palm vein is particularly chosen as a biometric trait along with widely used face and fingerprint because it is unique and is impossible to forge the vein pattern of an individual. Curvelet and Wavelet Transforms are used for the feature extraction. Experimental results indicate a good level of security and recognition rate of 91% and 89% is achieved on our own generated database. The results are promising when compared with other existing similar techniques.Reference to this paper should be made as follows: Inamdar, S.R. and Dandawate, Y.H. (2016) 'Multimodal biometric cryptosystem based on fusion of wavelet and curvelet features in robust security application', Int. He has 23 years of teaching experience and has published more than 55 papers 34 S.R. Inamdar and Y.H. Dandawate in reputed international and national conferences/referred journals. His areas of interest are in signal and image processing, embedded systems and soft computing. He is a reviewer and editorial board member of reputed journals in India and abroad. He is also working on several research projects. He is a senior member of IEEE and Fellow member of IETE, India.

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Fusion based Multimodal Biometric cryptosystem

Abstract: Security is main concern in Automated Teller

Cited by 16 publications

References 11 publications

Robust Iris and Fingerprint Biometric Fusion in Multimodal Feature Template Matching

Robust Iris and Fingerprint Biometric Fusion in Multimodal Feature Template Matching

Survey on Enhanced Cardless Transaction using Biometric ATMs

Multimodal biometric cryptosystem based on fusion of wavelet and curvelet features in robust security application

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