Method of vehicle identification and a system for vehicle identification
First Claim
1. A computer implemented 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 connected to a motion sensor and configured to be triggered the motion sensor;
converting the input image of the vehicle by a processor of a normalization unit to 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 sealed 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;
performing by a processor of a parameterization unit 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 (h) 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;
and determining the vehicle characteristic by a processor of a classification unit by comparing the parameters of a normalized image with parameters of reference images obtained from a reference database.
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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); normalization of the input image (301) of the vehicle in a normalization unit (103, 104) to obtain a normalized image; determining the vehicle characteristic in a classification unit (111, 112) by comparing parameters of a normalized image obtained in a parametrization unit (107, 108) with parameters of reference images obtained from a reference database (113, 114). Normalization in the normalization 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 normalization attributes defining at least one scaling coefficient (znorm, anorm, vnorm); choosing from the scaled image (307) a RoI area (308) of a normalized size and location dependent on the location of the registration plate area (303); and presenting data from the RoI area (308) as a normalized image (311).
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Citations
10 Claims
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1. A computer implemented 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 connected to a motion sensor and configured to be triggered the motion sensor; converting the input image of the vehicle by a processor of a normalization unit to 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 sealed 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;performing by a processor of a parameterization unit 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 (h) 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; and determining the vehicle characteristic by a processor of a classification unit by comparing the parameters of a normalized image with parameters of reference images obtained from a reference database. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. 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, the image source being connected to a motion sensor and configured to capture an image when the image source is triggered by the motion sensor; a normalization unit having a processor 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 having processor configured to determine the vehicle characteristic by comparing parameters of a normalized image obtained by a processor of a parameterization unit with parameters of reference images obtained from a reference database; wherein the processor of 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 (vin) 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