System and method for automatic camera health monitoring

• US 7,683,934 B2
• Filed: 12/06/2006
• Issued: 03/23/2010
• Est. Priority Date: 12/06/2005
• Status: Active Grant

• Current Assignee: March Networks Corporation (Infinova (Canada) Ltd.)
• Original Assignee: March Networks Corporation (Infinova (Canada) Ltd.)
• Inventors: Maughan, Kenneth Edward, MacLean, Roger Francis, Sun, Man-Yee, Montminy, Christian Joseph Eric
• Primary Examiner(s): Ho; Tuan
• Application Number:
  US11/567,353
• Publication Number:
  US 20070126869A1
• Time in Patent Office: 1,203 Days
• Field of Search: 348/143, 348/207.99, 348/241, 382/103, 375/240.16
• US Class Current: 348/207.99
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G08B 13/196 using television cameras
• CPC Class Codes: G08B 29/04 Monitoring of the detection circuits
• CPC Class Codes: G08B 29/26 by updating and storing reference thresholds
• CPC Class Codes: H04N 17/002 for television cameras
• CPC Class Codes: H04N 23/60 Control of cameras or camera modules
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

A system and method are provided for automatic camera health monitoring, such as for a camera in a video surveillance system. The system preferably provides substantially continuous monitoring and detection of camera malfunction, due to either external or internal conditions. Camera malfunction is detected when a computed camera health measurement exceeds a malfunction threshold. The camera health measurement is computed based on a comparison of a current camera health record to a plurality of stored camera health records obtained in a learning mode, which characterize known states of normal camera operation. Aside from monitoring camera health, methods of the present invention can also be used to detect an object being added to or removed from a scene, or to detect a change in lighting in a scene, possibly caused by a defective light fixture.

Claims

1. A method of detecting camera malfunction in a digital video surveillance system, the method comprising:

generating a current camera health record based on current image data;

computing a camera health measurement based on a comparison of the current camera health record to a plurality of stored camera health records characterizing known states of normal camera operation; and

detecting a camera malfunction when the camera health measurement exceeds a malfunction threshold,

wherein generating the current camera health record comprises generating an anchor region by determining a region having a uniquely identifiable enemy of frequency components within an average frame,

wherein computing the camera health measurement comprises

calculating, for each possible position of an anchor-region sized window in a search area, a sum of square errors between reference image pixels in an anchor region and current image pixels in the position in the search area; and

storing each sum of square errors in an entry in an anchor region correlation array.

2. The method of claim 1 wherein the step of detecting the camera malfunction is performed when the smallest value of the anchor region correlation array expressed as a percentage of a sum of all elements in the array exceeds a correlation threshold.

3. A method of detecting camera malfunction in a digital video surveillance system, the method comprising:

generating a current camera health record based on current image data;

computing a camera health measurement based on a comparison of the current camera health record to a plurality of stored camera health records characterizing known states of normal camera operation; and

detecting a camera malfunction when the camera health measurement exceeds a malfunction threshold,

wherein generating the current camera health record comprises generating an image focus level by performing an orthogonal transform on each frame and summing a square value of all non-DC components of the transformed signal, and

wherein computing the camera health measurement comprises computing an average image focus level for frames acquired during a reference data generation period.

4. The method of claim 3 wherein the step of detecting the camera malfunction is performed when a comparison of the generated image focus level to the average image focus level exceeds an image focus threshold.