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US8203602B2
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Depth-aware blur kernel estimation method for iris deblurring
Assignee: Robert Bosch GmbH
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Filing: 2009-02-06
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Granted: 2012-06-19
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Expires: 2029-02-06
Abstract
Abstract A method of estimating a blur kernel distribution for visual iris recognition includes determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens. The first relationship is used to estimate a second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution. A position of an eye of a living being at a future point in time is predicted. A focus position of the camera lens is adjusted based upon the predicted position of the eye. The camera lens with the adjusted focus position is used to produce an image of the living being's eye at the point in time. An actual position of the living being's eye at the point in time is sensed. The first relationship is used to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time. The second relationship is used to calculate a standard deviation defining a Gaussian blur kernel distribution. The calculating is based upon a difference between the adjusted focus position and the desired focus position of the lens.
Inventors
- 👤 Liu Ren
- 👤 Xinyu Huang
- 👤 Ruigang Yang
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-06 12:40
CPC Classifications
H; H04; H04N; H04N7/00; H04N7/18; G; G06; G06V; G06V40/00; G06V40/10; G06V40/18; G06V40/19; G06T; G06T5/00; G06T5/73; G06T2207/00; G06T2207/10; G06T2207/10016; G06T2207/10028; G06T2207/10048; G06T2207/30; G06T2207/30196; G06T2207/30201
Claims Analysis
Total Claims: 8
Claim 1
Independent Claim
229 words
A method of estimating a blur kernel distribution for visual iris recognition, said method comprising the steps of: determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens; using the first mathematical relationship to estimate a second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution; predicting a position of an eye of a living being at a future point in time; adjusting a focus position of the camera lens based upon the predicted position of the eye; using the camera lens with the adjusted focus position to produce an image of the living being's eye at the point in time; sensing an actual position of the living being's eye at the point in time; using the first mathematical relationship to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time; using the second mathematical relationship to calculate a standard deviation defining a Gaussian blur kernel distribution, the calculating being based upon a difference between the adjusted focus position and the desired focus position of the lens; and digitally unblurring the produced image by using the blur kernel distribution defined by the calculated standard deviation.
Claim 2
Independent Claim
229 words
A method of estimating a blur kernel distribution for visual iris recognition, said method comprising the steps of: determining a first mathematical relationship between an in-focus position of a camera lens and a distance between the lens and an iris whose image is to be captured by the lens; using the first mathematical relationship to estimate a second mathematical relationship between the in-focus position of the lens and a standard deviation defining a Gaussian blur kernel distribution; predicting a position of an eye of a living being at a future point in time; adjusting a focus position of the camera lens based upon the predicted position of the eye; using the camera lens with the adjusted focus position to produce an image of the living being's eye at the point in time; sensing an actual position of the living being's eye at the point in time; using the first mathematical relationship to ascertain a desired focus position of the lens based upon the actual position of the living being's eye at the point in time; using the second mathematical relationship to calculate a standard deviation defining a Gaussian blur kernel distribution, the calculating being based upon a difference between the adjusted focus position and the desired focus position of the lens; and digitally unblurring the produced image by using the blur kernel distribution defined by the calculated standard deviation.
Claim 3
Dependent Claim
16 words
The method of claim 1 wherein the first mathematical relationship is determined based on empirical data.
Claim 4
Dependent Claim
14 words
The method of claim 1 wherein the second mathematical relationship is a linear relationship.
Claim 5
Dependent Claim
21 words
The method of claim 1 wherein a fixed position is used as a proxy for the predicted position of the eye.
Claim 6
Dependent Claim
20 words
The method of claim 1 wherein the first mathematical relationship is used in adjusting the focus position of the camera.
Claim 7
Dependent Claim
15 words
The method of claim 1 wherein the sensing step is performed using a depth sensor.
Claim 8
Dependent Claim
44 words
The method of claim 1 comprising the further step of determining whether the captured image needs to be modified based on the estimated blur kernel, which is realized by identifying a defocus-blur level of the captured iris image based on the estimated blur kernel.
References Cited (Backward Citations)
US20100202667A1
Cited
US20100202666A1
Cited
US7912252B2
Cited
US20110128365A1
Cited
US8059870B2
Cited
US20120027266A1
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2015-06-19 | 2015-12-19 | 2016-06-19 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2019-06-19 | 2019-12-19 | 2020-06-19 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2023-06-19 | 2023-12-19 | 2024-06-19 | $7700.00 | Window Closed / Lapsed |