Help removing/reducing noise in digitized data

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Hello community,
I have question regarding a project I'm working on. I have recently digitized a series of pictures of an insect walking (digitized the ends of each leg), however ,due to being unable to click on the exact same spot every time (while using ginput) there is some noise in the data. I'm trying to create a routine that lets me know when each leg is moving and when it's not moving, however, this noise makes it difficult to do.
Is there a way of removing this noise, or a way of predicting where the leg should be next so that the noise doesn't have an effect?
  9 Comments
Jan
Jan on 22 Sep 2011
@Guillermo: The question is not precise as you can see by the best possible answer: "yes".
Creating a meaningful answer would be easier, if you concentrate on a specific problem. If you want to apply smoothing, that all details about the insect are confusing: You want to filter a matrix of X- and Y-values. If you want to do the marking or the foot automatically, then it would be helpful if you explain the available input, e.g. frequency, resolution and color depth of the images. And example image might be helpful also.
Guillermo
Guillermo on 22 Sep 2011
@Jan Simon, I was originally interested in the first option, about smoothing, however, if it were possible to mark the foot automatically, that would make my life easier in the long run. The images we are currently analyzing are from a black and white video taken at a frequency of 10 frames/second, with a resolution of 1250 x 980. here's a zip file with some example images:
http://www.sendspace.com/file/92avwu

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