Object detection

• US 6,711,279 B1
• Filed: 11/17/2000
• Issued: 03/23/2004
• Est. Priority Date: 11/17/2000
• Status: Expired due to Term

• Current Assignee: Columbia Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Honeywell International Inc.
• Inventors: Cofer, Darren Duane, Hamza, Ridha M.
• Primary Examiner(s): COUSO, YON JUNG
• Application Number:
  US09/716,002
• Time in Patent Office: 1,222 Days
• Field of Search: 382/103, 382/141-144, 382/181, 382/282, 382/283, 348/135, 348/136, 348/143, 348/148, 348/149, 348/152
• US Class Current: 382/103
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G08B 13/19602 Image analysis to detect motion of the intruder, e.g. by frame subtraction
• CPC Class Codes: G08B 13/19604 involving reference image or background adaptation with time to compensate for changing conditions, e.g. reference image update on detection of light level change
• CPC Class Codes: G08B 13/19606 Discriminating between target movement or movement in an area of interest and other non-signicative movements, e.g. target movements induced by camera shake or movements of pets, falling leaves, rotating fan

Abstract

A method for object detection that utilizes a patterned background. Patterned backgrounds are chosen such that each reference image analyzed will have both light and dark pixels. The method calculates the difference between the expected value for the light pixels and the expected value of the dark pixels in the reference image. This difference is used to chose a threshold value. The difference in expected values for the corresponding pixels in a live image is calculated and compared to the threshold value. If the difference in expected values of the live image are less than the threshold value, object detection is indicated.

Claims

1. A method for detecting an object in an area, comprising:

a) capturing a reference image of a patterned background having both light areas and dark areas;

b) calculating a value γ

_ref representing the difference between the expected value of the brightness levels corresponding to the light areas in the reference image and the expected value of the brightness levels of the dark areas in the reference image;

c) capturing a live image;

d) calculating a value representing the difference between the expected value for the brightness levels in the live image corresponding to the light area of the reference image and the expected value for the brightness levels in the live image corresponding to the dark areas in the reference image; and

e) indicating an object has been detected when the value calculated in d) is less than a threshold T, where 0<

T<

γ

_ref.

2. A method according to claim 1, wherein the patterned background contains an approximately equal amount of light areas and dark areas.

3. A method according to claim 1, wherein the size of the captured images are no bigger than the approximate size of the smallest object for which detection is desired.

4. A method according to claim 1, wherein T is equal to about γ

_ref/2.

5. A method according to claim 1, wherein steps c), d), and e) are each performed two or more times for each time steps a) and b) are performed.

6. A method for detecting an object in an area, comprising:

a) capturing reference images for each of a plurality of area portions, the plurality of area portions covering the area, each portion having both light areas and dark areas;

b) for each reference image, calculating a value γ

_ref representing the difference between the expected value of the brightness levels corresponding to the light areas in the reference image and the expected value of the brightness levels of the dark areas in the reference image;

c) for each reference images, capturing a corresponding live image from the same area portion from which the reference image was captured;

d) for each pair of reference images and corresponding live image, calculating a value representing the difference between the expected value for the brightness levels in the live image corresponding to the light areas of the reference image and the expected value for the brightness levels in the live image corresponding to the dark areas in the reference image; and

e) indicating an object has been detected when the value calculated in d) for any pair of images is less than a threshold T, where 0<

T<

γ

_ref.

7. A method according to claim 6, wherein each of the plurality of area portions contains approximately equal amounts of light areas and dark areas.

8. A method according to claim 6, wherein the size of the area portions is no bigger than the approximate size of the smallest object for which detection is desired.

9. A method according to claim 6, wherein T is equal to about γ

_ref/2.

10. A method according to claim 6, wherein steps c), d), and e) are each performed two or more times for each time steps a) and b) are performed.

11. A method according to claim 6, wherein each of the plurality of area portions overlaps at least one other area portion.

12. A method according to claim 6, wherein each of the plurality of area portions overlaps about one half of at least one other area portion.

13. A method according to claim 6, wherein the area comprising the plurality of area portions surrounds a second area.

14. An object detection system, comprising:

a) an image capture device adapted to capture reference images of a patterned background having both light areas and dark areas, and further adapted to capture live images; and

b) an image analysis device adapted to calculate a value γ

_ref representing the difference between the expected value of the brightness levels corresponding to the light areas in a reference image and the expected value of the brightness levels of the dark areas in the reference image, further adapted to calculate a value D representing the difference between the expected value for the brightness levels in a live image corresponding to the light area of the reference image and the expected value for the brightness levels in the live image corresponding to the dark areas in the reference image, and further adapted to indicate an object has been detected when the value D is less than a threshold T, where 0<

T<

γ

_ref.

15. An object detection system according to claim 14, wherein T is equal to about γ

_ref/2.