Method for fog detection

• US 9,384,401 B2
• Filed: 05/15/2014
• Issued: 07/05/2016
• Est. Priority Date: 11/16/2011
• Status: Active Grant

• Current Assignee: Bayerische Motoren Werke AG
• Original Assignee: Bayerische Motoren Werke AG
• Inventors: Pavlic, Mario
• Primary Examiner(s): Harandi, Siamak
• Assistant Examiner(s): PATEL, PINALBEN V
• Application Number:
  US14/278,792
• Publication Number:
  US 20140247968A1
• Time in Patent Office: 782 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle

Abstract

A method for detecting fog by use of a camera image or a video image includes the taking of a two-dimensional image with at least one color channel or several color channels as a function of two independent location coordinates. The method determines a two-dimensional gray-scale function for the at least one color channel or for each of the several color channels, which defines the value of the gray scale as a function of the two independent location coordinates of the two-dimensional image. Then, the method performs a two-dimensional Fourier transformation of the two-dimensional gray-scale function depending on two independent frequency coordinates.

Claims

1. A method for detecting fog by use of a camera image or a video image, the method comprising the acts of:

taking a two-dimensional image with at least one color channel or several color channels as a function of two independent location coordinates;

determining a two-dimensional gray-scale function for the at least one color channel or for each of the several color channels, which defines a value of the gray scale as a function of the two independent location coordinates of the two-dimensional image;

performing a two-dimensional Fourier transformation of the two-dimensional gray-scale function depending on two independent frequency coordinates;

scaling the two-dimensional gray-scale image to compensate intensity gradients of the gray scales by use of a low-pass filter and by use of a high-pass filter;

calculating a power spectrum as the square of the absolute value of the Fourier transform;

analyzing the power spectrum by use of digital image processing;

analyzing the power spectrum by use of a family of Gabor filters;

filtering the power spectrum by each Gabor filter of the family of Gabor filters over the two-dimensional frequency range, wherein a result of said filtering is a Gabor characteristic for each of the corresponding Gabor filters; and

reducing the Gabor characteristics by one of a main component analysis or a support vector method in the frequency domain to form reduced Gabor characteristics.

2. The method according to claim 1, wherein:

the Gabor characteristics or the reduced Gabor characteristics are multiplied by a predefined weighting function in order to compute a fog indicator,

the fog indicator is compared with a predefined threshold value, and

the method assigns a value for “

fog”

or another value for “

no fog”

with a confidence measurement to a classification variable.

3. The method according to claim 2, wherein:

the predefined weighting function and the predefined threshold value are predefined by an evaluation of the process by use of training data.

4. The method according to claim 1,

wherein reducing the Gabor characteristics is carried out by use of the main component analysis in the frequency domain to reduced characteristics.

5. The method according to claim 1, wherein:

the reduced characteristics are classified,

the classification is carried out by use of a linear classifier or a non-linear classifier,

the method assigns a value to a classification variable, and

a confidence measurement is assigned to the classification variable, and

the value of the classification variable scales with occurrence of fog or the density of fog with the confidence measurement.

6. A vehicle, comprising:

a control unit having a first data interface and a second data interface,

a camera- or video system coupled to the first data interface of the control unit, and

at least one driver assistance system coupled to the second data interface of the control unit, wherein the control unit is operatively configured to;

receive a two-dimensional image in real time via the first data interface from the camera or video system, with at least one color channel or several color channels as a function of two independent location coordinates;

determine a two-dimensional gray-scale function for the at least one color channel or for each of the several color channels, which defines a value of the gray scale as a function of the two independent location coordinates of the two-dimensional image;

perform a two-dimensional Fourier transformation of the two-dimensional gray-scale function depending on two independent frequency coordinates, wherein

the two-dimensional gray-scale image is scaled,

the scaling compensates intensity gradients of the gray scales by use of a low-pass filter and by use of a high-pass filter,

a power spectrum, which is the square of the absolute value of the Fourier transform, is calculated,

the power spectrum is analyzed by use of digital image processing,

the power spectrum is analyzed by use of a family of Gabor filters,

the power spectrum is filtered by use of each Gabor filter of the family of Gabor filters over the two-dimensional frequency range, wherein a result of said filtering is a Gabor characteristic for a corresponding Gabor filter,

the Gabor characteristics

are reduced by a main component analysis to form reduced Gabor characteristics,

the Gabor characteristics or the reduced Gabor characteristics are multiplied by a predefined weighting function in order to compute a fog indicator,

the fog indicator is compared with a predefined threshold value,

a value for “

fog”

or another value for “

no fog”

is assigned with a confidence measurement to a classification variable, and

the value of the classification variable is transmitted to the at least one driver assistance system via the second data interface, wherein

the at least one driver assistance system is configured to at least one of output a warning to the driver in the event of occurring fog, and operate in a configuration specified for occurring fog.

7. A vehicle, comprising:

a control unit having a first data interface and a second data interface,

a camera- or video system coupled to the first data interface of the control unit, and

at least one driver assistance system coupled to the second data interface of the control unit, wherein the control unit is operatively configured to;

receive a two-dimensional image in real time via the first data interface from the camera or video system, with at least one color channel or several color channels as a function of two independent location coordinates,

determine a two-dimensional gray-scale function for the at least one color channel or for each of the several color channels, which defines a value of the gray scale as a function of the two independent location coordinates of the two-dimensional image,

perform a two-dimensional Fourier transformation of the two-dimensional gray-scale function depending on two independent frequency coordinates,

scale the two-dimensional gray-scale image,

the scaling compensates intensity gradients of the gray scales by use of a low-pass filter and by use of a high-pass filter,

calculate a power spectrum as the square of the absolute value of the Fourier transform,

analyze the power spectrum by use of digital image processing,

analyze the power spectrum by use of a family of Gabor filters,

filter the power spectrum by each Gabor filter of the family of Gabor filters over the two-dimensional frequency range, wherein a result of said filtering is a Gabor characteristic for each of the corresponding Gabor filters, and

reduce the Gabor characteristics by one of a main component analysis or a support vector method in the frequency domain to form reduced Gabor characteristics.