Iris Segmentation
The quality of eye image data become degraded particularly when the image is taken in the non-cooperative acquisition environment such as under visible wavelength illumination. Consequently, this environmental condition may lead to noisy eye images, incorrect localization of limbic and pupillary bou...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science Publishing Corporation
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25300/ http://umpir.ump.edu.my/id/eprint/25300/ http://umpir.ump.edu.my/id/eprint/25300/ http://umpir.ump.edu.my/id/eprint/25300/2/Iris%20Segmentation.pdf |
| Summary: | The quality of eye image data become degraded particularly when the image is taken in the non-cooperative acquisition environment such as under visible wavelength illumination. Consequently, this environmental condition may lead to noisy eye images, incorrect localization of limbic and pupillary boundaries and eventually degrade the performance of iris recognition system. Hence, this study has compared several segmentation methods to address the abovementioned issues. The results show that Circular Hough transform method is the best segmentation method with the best overall accuracy, error rate and decidability index that more tolerant to ‘noise’ such as reflection. |
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