METHOD OF VEHICLE IDENTIFICATION AND A SYSTEM FOR VEHICLE IDENTIFICATION
First Claim
1. A method for vehicle type identification to determine at least one vehicle characteristic, the method comprising:
- obtaining an input image of the vehicle from an image source;
normalization of the input image of the vehicle in a normalization unit to obtain a normalized image by;
reading normalization attributes (znorm, anorm, vnorm) from a unit for calibration of normalization attributes;
detecting a registration plate area within the input image processing the input image basing on normalization attributes defining at least one scaling coefficient (znorm, anorm, vnorm);
choosing from the scaled image a RoI area of a normalized size and location dependent on the location of the registration plate area;
and presenting data from the RoI area as a normalized image;
and determining the vehicle characteristic in a classification unit by comparing parameters of a normalized image obtained in a parameterization unit with parameters of reference images obtained from a reference database;
wherein;
the parameters of normalized image are obtained in the parameterization unit by;
performing a smoothing filtration of the normalized image to obtain a smoothed image (Ii);
determining oriented gradient images (Oi,j) of brightness change for the smoothed image (Ii) in different directions (j);
dividing the oriented gradient images (Oi,j) into blocks (Bi,j,n);
determining a column vector (vi,n) having R dimensions and defined as
vi,n=[∇
(Bi,0,n), . . . , ∇
(Bi,j,n)]reducing dimension of the column vector (vi,n) by left multiplication by a casting matrix Pi,n having S dimensions, wherein S is lower than R to obtain a column vector c(I)i,n defined as;
c(I)i,n=Pi,n·
*vi,n providing the column vector c as the output of the parameterisation unit describing parameters of the normalized image.
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Abstract
A method for vehicle identification to determine at least one vehicle characteristic, comprising: obtaining an input image (301) of the vehicle from an image source (101); normalisation of the input image (301) of the vehicle in a normalisation unit (103, 104) to obtain a normalized image; determining the vehicle characteristic in a classification unit (111, 112) by comparing parameters of a normalised image obtained in a parametrisation unit (107, 108) with parameters of reference images obtained from a reference database (113, 114). Normalisation in the normalisation unit (103, 104) comprises the steps of: detecting a registration plate area (303) within the input image (301); processing the input image (301) basing on normalisation attributes defining at least one scaling coefficient (znorm, anorm, vnorm); choosing from the scaled image (307) a RoI area (308) of a normalised size and location dependent on the location of the registration plate area (303); and presenting data from the RoI area (308) as a normalised image (311).
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Citations
14 Claims
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1. A method for vehicle type identification to determine at least one vehicle characteristic, the method comprising:
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obtaining an input image of the vehicle from an image source; normalization of the input image of the vehicle in a normalization unit to obtain a normalized image by; reading normalization attributes (znorm, anorm, vnorm) from a unit for calibration of normalization attributes; detecting a registration plate area within the input image processing the input image basing on normalization attributes defining at least one scaling coefficient (znorm, anorm, vnorm); choosing from the scaled image a RoI area of a normalized size and location dependent on the location of the registration plate area; and presenting data from the RoI area as a normalized image; and determining the vehicle characteristic in a classification unit by comparing parameters of a normalized image obtained in a parameterization unit with parameters of reference images obtained from a reference database; wherein; the parameters of normalized image are obtained in the parameterization unit by; performing a smoothing filtration of the normalized image to obtain a smoothed image (Ii); determining oriented gradient images (Oi,j) of brightness change for the smoothed image (Ii) in different directions (j); dividing the oriented gradient images (Oi,j) into blocks (Bi,j,n); determining a column vector (vi,n) having R dimensions and defined as
vi,n=[∇
(Bi,0,n), . . . , ∇
(Bi,j,n)]reducing dimension of the column vector (vi,n) by left multiplication by a casting matrix Pi,n having S dimensions, wherein S is lower than R to obtain a column vector c(I)i,n defined as;
c(I)i,n=Pi,n·
*vi,nproviding the column vector c as the output of the parameterisation unit describing parameters of the normalized image. - View Dependent Claims (2, 3, 4, 5, 7, 12, 13, 14)
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6. (canceled)
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8-10. -10. (canceled)
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11. A system for vehicle type identification to determine at least one vehicle characteristic, the system comprising:
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an image source providing an input image of the vehicle; a normalization unit configured to normalize of the input image of the vehicle to obtain a normalized image by; reading normalization attributes (znorm, anorm, vnorm) from a unit for calibration of normalization attributes; detecting a registration plate area within the input image processing the input image basing on normalization attributes defining at least one scaling coefficient (znorm, anorm, vnorm); choosing from the scaled image a RoI area of a normalized size and location dependent on the location of the registration plate area; and presenting data from the RoI area as a normalized image. and a classification unit configured to determine the vehicle characteristic by comparing parameters of a normalized image obtained in a parameterization unit with parameters of reference images obtained from a reference database; wherein the parameterization unit is further configured to; perform a smoothing filtration of the normalized image to obtain a smoothed image (Ii); determine oriented gradient images (Oi,j) of brightness change for the smoothed image (Ii) in different directions (i); divide the oriented gradient images (Oi,j) into blocks (Bi,j,n); determine a column vector (vi,n) having R dimensions and defined as
vi,n=[∇
(Bi,0,n), . . . , ∇
(Bi,j,n)]reduce dimension of the column vector (vi,n) by left multiplication by a casting matrix Pi,n having S dimensions, wherein S is lower than R to obtain a column vector c(I)i,n defined as;
c(I)i,n=Pi,n*vi,nprovide the column vector c as the output describing parameters of the normalized image.
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Specification