1. A review of soft computing techniques in biometrics
- Author
-
Tanvi, Neelam Goel, and Manvjeet Kaur
- Subjects
Soft computing ,Authentication ,Artificial neural network ,Biometrics ,Computer science ,business.industry ,Data_MISCELLANEOUS ,Feature extraction ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Evolutionary algorithm ,Machine learning ,computer.software_genre ,Fuzzy logic ,ComputingMethodologies_PATTERNRECOGNITION ,Feature (machine learning) ,Artificial intelligence ,business ,computer - Abstract
In this paper, a review of soft computing techniques in biometrics is presented. Biometrics has become one of the most promising authentication techniques in the last few years but issues like False Acceptance Rate, False Rejection Rate still prevails in biometrics. An efficient biometric system has higher recognition rate, tolerance for imprecision, uncertainty and noisy data. Recently, Soft Computing has gained wide popularity in biometric recognition where it has helped in improving the recognition rate to a great extent. Various soft computing techniques like fuzzy logic, evolutionary algorithm and artificial neural network has increasingly being used for the construction of efficient biometric systems. This paper first presents the introduction to biometrics along with the issues involved in it. A brief description of various soft computing techniques for feature extraction, fusion, feature optimization, improvement of recognition rate in biometrics is provided. Finally future research areas are presented.
- Published
- 2015