METHOD AND CAMERA ASSEMBLY FOR DETECTING RAINDROPS ON A WINDSCREEN OF A VEHICLE

• US 20150085118A1
• Filed: 09/07/2011
• Published: 03/26/2015
• Est. Priority Date: 09/07/2011
• Status: Abandoned Application

• Current Assignee: Valeo Schalter und Sensoren GmbH (Valeo SE)
• Original Assignee: Valeo Schalter und Sensoren GmbH (Valeo SE)
• Inventors: Ahiad, Samia, Robert-Landry, Caroline
• Application Number:
  US14/343,429
• Publication Number:
  US 20150085118A1
• Time in Patent Office: Days
• US Class Current: 348/148
• CPC Class Codes: B60R 1/10 Front-view mirror arrangements; specially adapted for covering the peripheral part of the vehicle B60R1/002; Periscope arrangements , i.e. optical devices using combinations of mirrors, lenses, prisms or the like specially adapted for covering the peripheral part of the vehicle B60R1/002; for viewing traffic-lights B60R1/005; Other mirror arrangements giving a view from above or under the vehicle
• CPC Class Codes: B60R 2300/304 using merged images, e.g. merging camera image with stored images
• CPC Class Codes: B60R 2300/8053 for bad weather conditions or night vision
• CPC Class Codes: B60S 1/0844 including a camera
• CPC Class Codes: G06F 18/2132 based on discrimination criteria, e.g. discriminant analysis
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle

Abstract

The invention concerns a method for detecting raindrops on a windscreen of a vehicle, in which an image of at least an area of the windscreen is captured, wherein at least one object its extracted from the captured image, and wherein ambient light conditions are determined (S12). At least one of at least two ways of object extraction (S14, S18) is performed in dependence on the ambient light conditions. Moreover, the invention concerns a camera assembly for detecting raindrops on a windscreen of a vehicle.

Claims

1. A method for detecting raindrops on a windscreen of a vehicle, in which an image of at least an area of the windscreen is captured by a camera, wherein at least one object is extracted from the captured image, and wherein ambient light conditions are determined, wherein at least one of at least two ways of object extraction is performed in dependence on the ambient light conditions.

2. The method according to claim 1, wherein at nocturnal or tunnel ambient light conditions with a number and/or a brightness of light sources below a predetermined threshold value, objects are extracted from the captured image by detecting objects a grey level of which is lower than a predetermined threshold value.

3. The method according to claim 1, wherein at nocturnal or tunnel ambient light conditions with a number and/or a brightness of light sources above a predetermined threshold value, objects are extracted from the captured image by detecting objects a grey level of which is higher than a predetermined threshold value.

4. The method according to claim 1, wherein at daylight ambient light conditions objects are extracted from the captured image by:

detecting an object'"'"'s dark part a grey level of which is lower than a predetermined threshold value; and

detecting an object'"'"'s bright part a grey level of which is higher than a predetermined threshold value, wherein

the dark part and the bright part of the object are merged.

5. The method according to claim 1, wherein the ambient light conditions are determined by means of the camera.

6. The method according to claim 1, wherein the ambient light conditions are determined quantitatively or qualitatively.

7. The method according to claim 1, wherein the objects are extracted using a segmentation of the captured image by region and/or a segmentation of the captured image by edges.

8. The method according to claim 1, wherein the extracted objects are classified in order to detect raindrops.

9. A camera assembly for detecting raindrops on a windscreen of a vehicle, comprising;

a camera for capturing an image of at least an area of the windscreen, processing means configured to extract at least one object from the captured image, and means for determining ambient light conditions,

wherein the processing means are configured to perform at least one of at least two ways of object extraction in dependence on the ambient light conditions.