Abstract
In recent years, the need for security of personal data is becoming progressively important. A biometric system is an evolving technology that is used in various fields like forensics, secured area and security system. With respect to this concern, the identification system based on the fusion of multibiometric values is the most recommended in order to significantly improve and obtain high performance accuracy. The main purpose of this research work is to design and propose a hybrid system of combining the effect of three effective models: Retinex Algorithm, Stacked Deep Auto Encoder and Random forest (RF) classifier based on multi-biometric fingerprint as well as finger-vein recognition system. According to literature several fingerprint as well as fingervein recognition system are designed that uses various techniques in order to reduce false detection rate and to enhance the performance of the system. A comparative study of different recognition technique along with their limitations is also summarized and optimum approach is proposed which may enhance the performance of the system. In order to gain above mentioned objectives, fingerprint and fingervein dataset is taken for training and testing. The result analysis shows approx. 97% accuracy, 92% precision rate as well as 0.04 EER that shows enhancement over existing work.
Highlights
Biometric recognition refers to the use of characteristic anatomical features and behavioral features that are used as identifiers or biometric features or features to automatically recognize people to be designated
Biometrics is a technology which identifies a person based on his physiology or behavioral characteristics
A recognition system that uses Retinex, SDAE and Random forest (RF) models and a multimodal biometric identification system based on the fusion of fingerprints and fingervein were introduced
Summary
Biometric recognition refers to the use of characteristic anatomical features (e.g. fingerprints, face, iris) and behavioral features (e.g. language) that are used as identifiers or biometric features or features to automatically recognize people to be designated. Biometrics is becoming an essential part of effective solutions for personal identification, as biometric identifiers cannot be transmitted or moved and reflect the individual's physical identity. The recognition of a person through his body and the subsequent connection of this body with an "identity" established from the outside constitutes a very powerful tool for identity management with enormous potential positive and negative consequences [1]. Biometrics is a fascinating problem in model recognition research, but if applied with care, it is a technology that can make our society safer, less fraudulent and more user-friendly [2]. Numerous biometric authentication systems have been used, but each type of unimodal biometrics has its disadvantages depending on the characteristics, the recording device, the database and the characteristics of these characteristics [3].
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