First we gather a data set of all the hand-shapes we wish to recognise. A naive approach to recognizing a new image D would be to simply compare it with all the images stored in the data set and find the target image T with the closest match. But because there are so many images in the data set this will take far too long. We can reduce the time by using a multi-scale approach. We divide up the data set into groups of images, which are similar to one another by blurring the images at different levels so that small differences between similar images will be eroded.
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