19-03-2014, 11:11 AM
FAST MULTIMODAL BIOMETRIC APPROACH USING DYNAMIC FINGERPRINT AUTHENTICATION AND ENHANCED IRIS FEATURES
Abstract
Unimodal biometric systems have variety of problems such as noisy data, intra-class variations, restricted degree of freedom, non-universality, spoof attacks, and unacceptable error rates. Multimodal biometrics refers the combination of two or more biometric modalities in a single identification system. Biometric identification system based on the pattern of the human iris and fingerprint are well suited for a high level of security systems. However, the multimodal biometric system is limited to the time constraints due to its multiple processing stages. To overcome the problem of time taken we present a fast multimodal verification system by using the dynamic regions of the fingerprint image and enhanced iris segmentation method. This paper proposes enhanced fingerprint and iris recognition system that implements a fusion of both iris and fingerprint images at score level. The simulations are performed in the MATLAB environment to evaluate the performance of the implemented algorithms. Results and observations of the fusion are presented at the end.
Introduction:
Biometrics are technologies used for measuring and analyzing a person's unique characteristics and is usually associated with the use of unique physiological characteristics to identify an individual.
The paper is organized as follows. A typical biometric system is discussed ,with the need of multimodal biometrics is illustrated in Multimodal biometric system and different fusion techniques are mentioned with the description of score level fusion technique , challenges and conclusions are presented in the last section of the paper.
Biometrics is used for maintaining security at different levels. It is used in measuring features like face fingerprints, hand geometry, handwriting, iris, retinal, vein, voice etc. As the need of security is tremendously increasing and as well as transaction, frauds are increasing, the need for highly secure identification and personal verification technologies is becoming apparent. Prevailing methods of human identification based on credentials (identification documents and PIN) are not able to meet the growing demands for stringent security in applications such as national ID cards, border crossings, government benefits, and access control. As a result, biometric recognition, or simply biometrics, which is based on physiological and behavioral characteristics of a person, is being increasingly adopted and mapped to rapidly growing person identification applications. Although there are demerits in using biometric system such as noise in sensed data, intra-class variations, distinctiveness, non-universality, spoof attacks etc.
Challenges to Multi-Biometric System
Followings are the challenges in designing the multi modal system:
1. The information obtained from different biometric sources can be combined at different levels therefore selecting the best level of fusion will have the direct impact on performance and cost involved In developing a system.
2. There are Numbers of techniques available for fusion in multi-biometric system and the multiple source of information is available. Hence it is challenging to find the optimal solution for the application provided.
3. In multi-biometric systems the information acquired from different sources can be processed either in sequence or parallel. Hence it is challenging to decide about the processing architecture to be employed in designing the multi-biometric system.
Iris Recognition:
Iris Recognition is the process of recognizing a person by analyzing the random patterns of the iris. The automated method of iris recognition is relatively young existing in patent since 1994 only.
The iris is the muscle in the eye that regulates the size of the pupil, controlling the amount of eye that enters the eye. It is the colored portion of the eye with the coloring amount based on the melatonin pigment present in the muscle. Although the coloration and structure of iris is genetically linked, the details of the pattern are not. The individual irises are unique and structurally different, which allows for it to be used for the recognition purposes.
Multimodal Biometric System:
Multimodal biometric systems are those that utilize more than one physiological or behavioral characteristic for enrollment, verification, or identification. In applications such as border entry/exit, access control, civil identification, and network security, multi-modal biometric systems are looked to as a means of reducing false non-match and false match rates, providing a secondary means of enrollment, verification, and identification if sufficient data cannot be acquired from a given biometric sample, and combating attempts to fool biometric systems through fraudulent data sources such as fake fingers.
Abstract
Unimodal biometric systems have variety of problems such as noisy data, intra-class variations, restricted degree of freedom, non-universality, spoof attacks, and unacceptable error rates. Multimodal biometrics refers the combination of two or more biometric modalities in a single identification system. Biometric identification system based on the pattern of the human iris and fingerprint are well suited for a high level of security systems. However, the multimodal biometric system is limited to the time constraints due to its multiple processing stages. To overcome the problem of time taken we present a fast multimodal verification system by using the dynamic regions of the fingerprint image and enhanced iris segmentation method. This paper proposes enhanced fingerprint and iris recognition system that implements a fusion of both iris and fingerprint images at score level. The simulations are performed in the MATLAB environment to evaluate the performance of the implemented algorithms. Results and observations of the fusion are presented at the end.
Introduction:
Biometrics are technologies used for measuring and analyzing a person's unique characteristics and is usually associated with the use of unique physiological characteristics to identify an individual.
The paper is organized as follows. A typical biometric system is discussed ,with the need of multimodal biometrics is illustrated in Multimodal biometric system and different fusion techniques are mentioned with the description of score level fusion technique , challenges and conclusions are presented in the last section of the paper.
Biometrics is used for maintaining security at different levels. It is used in measuring features like face fingerprints, hand geometry, handwriting, iris, retinal, vein, voice etc. As the need of security is tremendously increasing and as well as transaction, frauds are increasing, the need for highly secure identification and personal verification technologies is becoming apparent. Prevailing methods of human identification based on credentials (identification documents and PIN) are not able to meet the growing demands for stringent security in applications such as national ID cards, border crossings, government benefits, and access control. As a result, biometric recognition, or simply biometrics, which is based on physiological and behavioral characteristics of a person, is being increasingly adopted and mapped to rapidly growing person identification applications. Although there are demerits in using biometric system such as noise in sensed data, intra-class variations, distinctiveness, non-universality, spoof attacks etc.
Challenges to Multi-Biometric System
Followings are the challenges in designing the multi modal system:
1. The information obtained from different biometric sources can be combined at different levels therefore selecting the best level of fusion will have the direct impact on performance and cost involved In developing a system.
2. There are Numbers of techniques available for fusion in multi-biometric system and the multiple source of information is available. Hence it is challenging to find the optimal solution for the application provided.
3. In multi-biometric systems the information acquired from different sources can be processed either in sequence or parallel. Hence it is challenging to decide about the processing architecture to be employed in designing the multi-biometric system.
Iris Recognition:
Iris Recognition is the process of recognizing a person by analyzing the random patterns of the iris. The automated method of iris recognition is relatively young existing in patent since 1994 only.
The iris is the muscle in the eye that regulates the size of the pupil, controlling the amount of eye that enters the eye. It is the colored portion of the eye with the coloring amount based on the melatonin pigment present in the muscle. Although the coloration and structure of iris is genetically linked, the details of the pattern are not. The individual irises are unique and structurally different, which allows for it to be used for the recognition purposes.
Multimodal Biometric System:
Multimodal biometric systems are those that utilize more than one physiological or behavioral characteristic for enrollment, verification, or identification. In applications such as border entry/exit, access control, civil identification, and network security, multi-modal biometric systems are looked to as a means of reducing false non-match and false match rates, providing a secondary means of enrollment, verification, and identification if sufficient data cannot be acquired from a given biometric sample, and combating attempts to fool biometric systems through fraudulent data sources such as fake fingers.