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Content Provider | IEEE Xplore Digital Library |
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Author | Teh Wei Hsiung Mohamed, S.S. |
Copyright Year | 2011 |
Description | Author affiliation: School of Science, Information & Engineering, KDU College, Penang, MALAYSIA (Teh Wei Hsiung; Mohamed, S.S.) |
Abstract | The biometric identification system is one of the technology used in the recognition system. Iris recognition system is the most reliable system for an individual identification. Nowadays, many applications have been implemented with this feature such as the time attendance system for high security environment, hospitals, airports, government agencies, educational facilities, and etc. The conventional method applied on the security is not reliable such as the passwords may be forgotten or hacked and ID cards may be lost or forged. The main purpose of this project is to achieve good quality performance of iris recognition using low resolution image for attendance monitoring system. This project apply two existing methods which are Hough Transform and Daugman's Integro Differential Operator to identify the best technique of iris detection using low resolution image as input. The results show that these techniques capable to recognize the low resolution iris with the accuracy of 100% when applied Hough Transform compared to the Daugman's Integro Differential Operator with only 86.88%. |
Starting Page | 612 |
Ending Page | 617 |
File Size | 1459036 |
Page Count | 6 |
File Format | |
ISBN | 9781457720581 |
e-ISBN | 9781457720598 |
DOI | 10.1109/ICCAIE.2011.6162207 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-12-04 |
Publisher Place | Malaysia |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image segmentation Gabor filter Image resolution Accuracy Hamming Distance Hough Transform Daugman's Rubber Sheet Model Biometric technologies High definition video Daugman's Integro Differential Operator Iris recognition |
Content Type | Text |
Resource Type | Article |
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