Video analysis

1. A method, comprising:

capturing a frame from a first video device, said frame representing a test pattern;

determining at least one captured color for at least one pixel of said captured frame;

providing a reference pixel including at least one reference color, said reference pixel determined by statistical analysis of said first signals from a population of second video devices that have received said test pattern;

determining a relation between said captured color value and said reference color;

comparing said relation with a threshold value; and

storing said relation.

2. The method of claim 1 , further comprising adjusting said threshold value using a standard deviation of a distribution from said population of second video devices.

3. The method of claim 1 , further comprising receiving a plurality of second signals from the first video device; wherein said frame is captured from the second signals.

4. The method of claim 3 , wherein said plurality of second signals comprises at least one of a composite signal, a separated video (S-Video) signal, and a red-green-blue component signal.

5. The method of claim 3 , wherein said plurality of second signals comprises at least two of a composite signal, a separated video (S-Video) signal, and a red-green-blue component signal.

6. The method of claim 3 , wherein said plurality of second signals comprises at least two categories of video signals presenting the same image.

7. The method of claim 1 , wherein said one reference color includes a primary color.

8. The method of claim 1 , wherein said statistical analysis comprises generating a Gaussian curve and calculating a standard deviation based on the first signals.

9. A method, comprising:

generating a pixilated reference frame based on samples from a population of video devices, said pixilated reference frame based on an averaged video image and at least one standard deviation from a color-based population density function for each pixel;

obtaining a capture frame from each of said plurality of video devices;

comparing at least one pixel of said capture frame to said pixilated reference frame to produce a pixel error; and

determining if said pixel error is greater than a threshold.

10. The method of claim 9 , wherein said pixel error is based on a comparison of a color component of said at least one pixel and said pixilated reference frame.

11. The method of claim 9 , further comprising defining a pixel capture region of said capture frame, wherein said at least one pixel is chosen from said pixel capture region.

12. The method of claim 9 , further comprising:

adjusting said threshold such that a predetermined percentage of said video devices tested includes a pixel error less than said threshold.

13. The method of claim 9 , wherein said capturing at least one pixel of said capture frame updates said reference frame.

14. The method of claim 9 , wherein receiving a capture frame from each of said video devices includes sampling at least two categories of video signals presenting substantially the same image.

15. The method of claim 9 , wherein receiving a capture frame from each of said video devices includes sampling at least two of a composite signal, S-Video signals, and red-green-blue component signal.

16. The method of claim 9 , wherein said averaged video image comprises at least one average pixel value for a plurality of video frames, and said at least one color-based population density function for each pixel comprises a Gaussian distribution.

17. A system, comprising:

a database including a reference file having at least a pixilated reference frame that is based on samples from a population of video devices, said pixilated reference frame based on an averaged video image and at least one standard deviation from a color-based population density function for each pixel;

an interface that selectively obtains a capture frame;

a computing device that includes the interface and that is in selective communication with the database; said computing device configured at least to compare at least one pixel of said capture frame to said pixilated reference frame to produce a pixel error; and to determine if said pixel error is greater than a threshold.

18. The system of claim 17 , said computing device further configured to determine said pixel error based on a comparison of a color component of said at least one pixel and said pixilated reference frame.

19. The system of claim 17 , said computing device further configured to define a pixel capture region of said capture frame, wherein said at least one pixel is chosen from said pixel capture region.

20. The system of claim 17 , said computing device further configured to adjust said threshold such that a predetermined percentage of said video devices tested includes a pixel error less than said threshold.

21. The system of claim 17 , said computing device further configured to update said reference frame using at least one pixel of said capture frame.

22. The system of claim 17 , said computing device further configured to receive a capture frame from each of said video devices by sampling at least two types of video outputs presenting substantially the same image.

23. The system of claim 17 , said computing device further configured to obtain a capture frame from each of said video devices including sampling at least two of a composite output, S-Video outputs, and component outputs.

24. The system of claim 17 , wherein said averaged video image comprises at least one average pixel value for a plurality of video frames, and said at least one color-based population density function for each pixel comprises a Gaussian distribution.