1. An LED lamp comprising:
an LED module including a board and a plurality of LEDs annularly arranged and mounted on a front surface of the board, the board having an opening at an area of the board surrounded by the LEDs; and
a light guide including a base portion and a light leading portion integrated with the base portion and extending from the base portion toward an outer periphery of the board and in a direction away from the front surface of the board,
the light guide being engaged with and fastened to the front surface side of the board at the opening, and being configured to guide a part of light emitted by the LEDs through the light leading portion and a part of the light emitted by the LEDs over an outer edge of the board.
2. The LED lamp of claim 1, wherein the light guide includes a hook portion engaged with an edge of the board defining the opening.
3. The LED lamp of claim 2, wherein a gap is formed between the hook portion and the edge of the board defining the opening in a direction along the front surface of the board.
4. The LED lamp of claim 2, wherein the hook portion has at least two hooks are arranged at positions symmetrical with each other with respect to a center of the opening.
5. The LED lamp of claim 1, wherein the LED module includes a connector arranged on the board at the area of the board surrounded by the LEDs, and the connector is connected to a plug passing through the opening.
6. The LED lamp of claim 1, further comprising:
a base body configured to be thermally connected to the LED module and to release heat generated by the LEDs.
7. The LED lamp of claim 6, wherein
the base body has a contact surface configured to cover at least an area in the rear surface of the board corresponding to an area on which the LEDs are mounted.
8. The LED lamp of claim 1, wherein
the light guide is made of a transparent material.
9. The LED lamp of claim 1, wherein
the LED module further includes a connector disposed at the area of the board surrounded by the LEDs, and
the base portion of the light guide is disposed between the LEDs and the connector.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
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; and
performing a two-dimensional Fourier transformation of the two-dimensional gray-scale function depending on two independent frequency coordinates.
2. The method according to claim 1, wherein:
the two-dimensional gray-scale image is scaled, and
the scaling compensates intensity gradients of the gray scales by use of a low-pass filter and by use of a high-pass filter.
3. The method according to claim 2, wherein:
the square of the absolute value of the Fourier transform, which is called a power spectrum, is calculated, and
the power spectrum is analyzed by use of digital image processing.
4. The method according to claim 3, wherein:
the power spectrum is analyzed by use of a family of Gabor filters, and
the power spectrum is filtered by use of each Gabor filter of the family of Gabor filters over the two-dimensional frequency range, and the filtering result is called a Gabor characteristic for this Gabor filter.
5. The method according to claim 4, wherein:
the Gabor characteristics are characteristics-reduced, and
the reduction of characteristics is carried out by means of a main component analysis to reduced Gabor characteristics.
6. The method according to claim 5, wherein:
the Gabor characteristics or the characteristics-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 \u201cfog\u201d or another value for \u201cno fog\u201d with a confidence measurement to a classification variable.
7. The method according to claim 6, wherein:
the predefined weighting function and the predefined threshold value are predefined by an evaluation of the process by use of training data.
8. The method according to claim 3, wherein:
the power spectrum is characteristics-reduced, and
the reduction of characteristics is carried out by use of a main component analysis in the frequency domain to reduced characteristics.
9. The method according to claim 3, wherein:
the power spectrum is characteristics-reduced, and
the reduction of characteristics is carried out by use of a support vector method in the frequency domain to reduced characteristics.
10. The method according to claim 9, 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,
a confidence measurement is assigned to the classification variable, and
the value of the classification variable scales with the occurrence of fog or the density of fog with the confidence measurement.
11. A vehicle, comprising:
a control unit,
a camera- or video system, and
at least one driver assistance system, wherein the control unit is operatively configured to execute processing in real-time that:
receives a two-dimensional image, taken via 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
the square of the absolute value of the Fourier transform, which is called a power spectrum, 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, and the filtering result is called a Gabor characteristic for this Gabor filter,
the Gabor characteristics are characteristics-reduced,
the reduction of characteristics is carried out by means of a main component analysis to reduced Gabor characteristics,
the Gabor characteristics or the characteristics-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,
the method assigns a value for \u201cfog\u201d or another value for \u201cno fog\u201d with a confidence measurement to a classification variable, and
transmits the value of the classification variable to the at least one driver assistance system, wherein
the at least one driver assistance system outputs a warning to the driver in the event of occurring fog, andor the driver assistance system can be operated in a configuration specified for occurring fog.