Bi-Local Region Based Iris Segmentation Framework for Less-Constrained Visible Wavelength Images
Iris recognition systems often degrade in performance when the subjects' cooperation is not expected in a less-constrained environment captured from a greater distance by visible wavelength imaging system. Algorithms in this field have reported inaccurate segmentations due to non-circular geome...
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| Published in: | 7th International Conference on Imaging for Crime Detection and Prevention (ICDP 2016) p. 22 |
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| Main Authors: | , , , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
Stevenage, UK
IET
2016
The Institution of Engineering & Technology |
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| ISBN: | 1785614002, 9781785614002 |
| Online Access: | Get full text |
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| Abstract | Iris recognition systems often degrade in performance when the subjects' cooperation is not expected in a less-constrained environment captured from a greater distance by visible wavelength imaging system. Algorithms in this field have reported inaccurate segmentations due to non-circular geometry of the iris and various noise factors introduced by non-cooperative subjects. In this paper, we propose a local region based active contour model to segment non-circular iris shape from visible wavelength images which are normally noisy and inhomogeneous. Accurate segmentation can be achieved through the proposed bi-local neighborhood approach which allows contour evolution using local region based terms while simultaneously avoiding occlusions without the need of separate image processing steps. B-spline formulation in this approach ensures simplicity and efficiency of this algorithm, thereby overcoming the limitations of active contour based methods in terms of computational power. The proposed algorithm has demonstrated good segmentation accuracy on NICE.I and NICE.II databases. |
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| AbstractList | Iris recognition systems often degrade in performance when the subjects' cooperation is not expected in a less-constrained environment captured from a greater distance by visible wavelength imaging system. Algorithms in this field have reported inaccurate segmentations due to non-circular geometry of the iris and various noise factors introduced by non-cooperative subjects. In this paper, we propose a local region based active contour model to segment non-circular iris shape from visible wavelength images which are normally noisy and inhomogeneous. Accurate segmentation can be achieved through the proposed bi-local neighborhood approach which allows contour evolution using local region based terms while simultaneously avoiding occlusions without the need of separate image processing steps. B-spline formulation in this approach ensures simplicity and efficiency of this algorithm, thereby overcoming the limitations of active contour based methods in terms of computational power. The proposed algorithm has demonstrated good segmentation accuracy on NICE.I and NICE.II databases. |
| Author | Goi, B.M Yeo, I Teng, K.S Chai, T.Y Tay, Y.H |
| Author_xml | – sequence: 1 givenname: T.Y surname: Chai fullname: Chai, T.Y organization: Lee Kong Chian Fac. of Eng. & Sci., Univ. Tunku Abdul Rahman, Kajang – sequence: 2 givenname: B.M surname: Goi fullname: Goi, B.M – sequence: 3 givenname: Y.H surname: Tay fullname: Tay, Y.H – sequence: 4 givenname: K.S surname: Teng fullname: Teng, K.S – sequence: 5 givenname: I surname: Yeo fullname: Yeo, I |
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| Copyright | Copyright The Institution of Engineering & Technology Nov 23, 2016 |
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| DOI | 10.1049/ic.2016.0090 |
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| Keywords | bilocal region based iris segmentation framework NICE.II database splines (mathematics) less-constrained visible wavelength image NICE.I database noncooperative subject image processing step visible wavelength imaging system image segmentation B-spline formulation iris recognition often system active contour based method contour evolution computational power iris noncircular geometry local region based active contour model iris recognition |
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| Snippet | Iris recognition systems often degrade in performance when the subjects' cooperation is not expected in a less-constrained environment captured from a greater... |
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| SubjectTerms | Algorithms Biometric recognition systems Computer vision and image processing techniques Contours Image processing Image recognition Image segmentation Interpolation and function approximation (numerical analysis) Object recognition Performance degradation Shape |
| Title | Bi-Local Region Based Iris Segmentation Framework for Less-Constrained Visible Wavelength Images |
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