Method for detecting accident

• US 20040234102A1
• Filed: 10/20/2003
• Published: 11/25/2004
• Est. Priority Date: 12/13/2002
• Status: Abandoned Application

• Current Assignee: LG CNS Company Limited (LBHunet Co., Ltd.)
• Original Assignee: LG CNS Company Limited (LBHunet Co., Ltd.)
• Inventors: Lee, Bong Keun
• Application Number:
  US10/689,497
• Publication Number:
  US 20040234102A1
• Time in Patent Office: Days
• US Class Current: 382/104
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles

Abstract

Disclosed is a method for detecting an accident more swiftly and reliably. The method for detecting an accident obtains an image from a predetermined region on a road, determining whether there exists an accident or not depending on change transition of gray levels for pixels on a line type trap set in advance on the basis of the obtained image. At the moment, a real vehicle and a shadow could be discriminated with use of quantity of change and frequency of the gray levels on the line type trap.

Claims

1. A method for detecting an accident comprising the steps of:

obtaining an image from a predetermined region on a road;

computing gray levels for each pixel corresponding to a predetermined line type trap from the obtained image; and

determining whether there exists an accident or not depending on change transition of the computed gray levels for a predetermined period of time.

2. The method according to claim 1, further comprising the step of displaying the obtained image on a screen.

3. The method according to claim 1, wherein the line type trap is set on a lane.

4. The method according to claim 1, wherein the computed gray levels are average values of gray levels for one pixel or a predetermined number of pixels existing in back and forth of the one pixel.

5. The method according to claim 1, wherein the set line type trap includes pixels arranged in a row.

6. A method for detecting an accident comprising the steps of:

obtaining an image from a predetermined region on a road;

computing gray levels for each pixel corresponding to a predetermined line type trap from the obtained image;

tracking a vehicle using quantity of change for the computed gray levels; and

determining whether there exists an accident or not by tacking the gray levels for the tracked vehicle for a predetermined period of time.

7. The method according to claim 6, further comprising the step of displaying the obtained image on a screen.

8. The method according to claim 6, wherein the line type trap is set on a lane.

9. The method according to claim 6, wherein the computed gray levels are average values of gray levels for one pixel or a predetermined number of pixels existing in back and forth of the one pixel.

10. The method according to claim 6, wherein the set line type trap includes pixels arranged in a row.

11. The method according to claim 6, further comprising the step of determining whether a vehicle is a real vehicle through comparison of gray level information for the traced vehicle included in the line type trap with gray level information for a real vehicle set in advance.

12. The method according to claim 11, wherein if the gray level information is in agreement with gray level information for a real vehicle set in advance, the tracked vehicle is determined to be a real vehicle.

13. The method according to claim 11, wherein the gray level information is quantity of change and frequency for the gray level.

14. The method according to claim 11, if the tracked vehicle is determined to be a real vehicle, a mark is made for a relevant vehicle on a screen corresponding to the determined vehicle.

15. The method according to claim 6, wherein if gray levels for the tracked vehicle do not change for a predetermined period of time, the tracked vehicle is determined to have caused an accident.