Error Correction on IRIS Biometric Template Using Reed Solomon Codes
| Autor: | Puteh Saad, Nazeema Abd Rahim, Sim Hiew Moi, Subariah Ibrahim |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Password
Authentication Theoretical computer science Biometrics urogenital system Computer science business.industry Data_MISCELLANEOUS fungi Feature extraction Iris recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition urologic and male genital diseases Iris flower data set female genital diseases and pregnancy complications ComputingMethodologies_PATTERNRECOGNITION Feature (computer vision) cardiovascular diseases Artificial intelligence Eye vein verification business |
| Zdroj: | 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation. |
| DOI: | 10.1109/ams.2010.50 |
| Popis: | Pin number or password that is used for authentication can be easily attacked. This limitation triggered the utilization of biometric for secured transactions. Biometric is unique to each individual and is reliable. Among the types of biometric being used currently, iris is the most accurate and it remains stable throughout a person’s life. However the major challenge on iris and other biometric for authentication is the intra user variability in the acquired identifiers. Iris of the same person captured at different time may differ due to the signal noise of the iris camera. Traditional cryptography method is unable to encrypt and store biometric template, then perform the matching directly. Minor changes in the bits of the feature set extracted from the iris may lead to a huge difference in the results of the encrypted feature. In our approach, an iris biometric template is secured using iris biometric and passwords. Error Correction Code, ECC is introduced to reduce the variability and noise of the iris data. Experimental results show that this approach can assure a higher security with a low false rejection or false acceptance rate. The successful iris recognition rate using this approach is up to 97%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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