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A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.8 pp.1450-1455

- Publication Date
- 1999/08/25

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- Special Section PAPER (Special Section on Digital Signal Processing)

- Category

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Jianyin LU, Yasuo YOSHIDA, "Blurred Image Recognition Based on Phase Invariants" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 8, pp. 1450-1455, August 1999, doi: .

Abstract: A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_8_1450/_p

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@ARTICLE{e82-a_8_1450,

author={Jianyin LU, Yasuo YOSHIDA, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={Blurred Image Recognition Based on Phase Invariants},

year={1999},

volume={E82-A},

number={8},

pages={1450-1455},

abstract={A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.},

keywords={},

doi={},

ISSN={},

month={August},}

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TY - JOUR

TI - Blurred Image Recognition Based on Phase Invariants

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 1450

EP - 1455

AU - Jianyin LU

AU - Yasuo YOSHIDA

PY - 1999

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E82-A

IS - 8

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - August 1999

AB - A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.

ER -