A method for vehicle type identification to determine at least one vehicle characteristic, comprising: - obtaining an input image of the vehicle from an image source; - normalisation of the input image of the vehicle in a normalisation unit (103, 104) to obtain a normalized image by: - reading normalization attributes (z norm, a norm, v norm) from a unit for calibration of normalization attributes; - detecting a registration plate area within the input image;processing the input image basing on normalisation attributes defining at least one scaling coefficient (z norm, a norm, v norm); - choosing from the scaled image a RoI area of a normalised size and location dependent on the location of the registration plate area; - and presenting data from the Rol area as a normalised image; - and 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); characterized in that: - the parameters of normalized image are obtained in the parametrisation unit (107, 108) by: o performing a smoothing filtration of the normalized image to obtain a smoothed image (I i); o determining oriented gradient images (O i,j) of brightness change for the smoothed image (I i) in different directions (j); o dividing the oriented gradient images (O i,j) into blocks (B i,j,n); ∘ determining a column vector (v i,n) having R dimensions and defined as v i, n = ∇ B i, 0, n,..., ∇ B i, j, n o reducing dimension of the column vector (v i,n) by left multiplication by a casting matrix P i,n having S dimensions, wherein S is lower than R to obtain a column vector c i,n defined as: c l i, n = P i, n * v i, n o providing the column vector c as the output of the parametrisation unit (107, 108) describing parameters of the normalised image. - obtaining an input image of the vehicle from an image source; - normalisation of the input image of the vehicle in a normalisation unit (103, 104) to obtain a normalized image by: - reading normalization attributes (z norm, a norm, v norm) from a unit for calibration of normalization attributes; - detecting a registration plate area within the input image;processing the input image basing on normalisation attributes defining at least one scaling coefficient (z norm, a norm, v norm); - choosing from the scaled image a RoI area of a normalised size and location dependent on the location of the registration plate area; - and presenting data from the Rol area as a normalised image; - reading normalization attributes (z norm, a norm, v norm) from a unit for calibration of normalization attributes; - detecting a registration plate area within the input image;processing the input image basing on normalisation attributes defining at least one scaling coefficient (z norm, a norm, v norm); - choosing from the scaled image a RoI area of a normalised size and location dependent on the location of the registration plate area; - and presenting data from the Rol area as a normalised image; - and 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); characterized in that: - the parameters of normalized image are obtained in the parametrisation unit (107, 108) by: o performing a smoothing filtration of the normalized image to obtain a smoothed image (I i); o determining oriented gradient images (O i,j) of brightness change for the smoothed image (I i) in different directions (j); o dividing the oriented gradient images (O i,j) into blocks (B i,j,n); ∘ determining a column vector (v i,n) having R dimensions and defined as v i, n = ∇ B i, 0, n,..., ∇ B i, j, n o reducing dimension of the column vector (v i,n) by left multiplication by a casting matrix P i,n having S dimensions, wherein S is lower than R to obtain a column vector c i,n defined as: c l i, n = P i, n * v i, n o providing the column vector c as the output of the parametrisation unit (107, 108) describing parameters of the normalised image. o performing a smoothing filtration of the normalized image to obtain a smoothed image (I i); o determining oriented gradient images (O i,j) of brightness change for the smoothed image (I i) in different directions (j); o dividing the oriented gradient images (O i,j) into blocks (B i,j,n); ∘ determining a column vector (v i,n) having R dimensions and defined as v i, n = ∇ B i, 0, n,..., ∇ B i, j, n o reducing dimension of the column vector (v i,n) by left multiplication by a casting matrix P i,n having S dimensions, wherein S is lower than R to obtain a column vector c i,n defined as: c l i, n = P i, n * v i, n o providing the column vector c as the output of the parametrisation unit (107, 108) describing parameters of the normalised image.