Interesting problem. The solution I would try is the following. 1. Apply a low pass filter, such as convolution with a 2D gaussian mask. This will give you

Interesting problem. The solution I would try is the following. 1. Apply a low pass filter, such as convolution with a 2D gaussian mask. This will give you a bunch of (probably, but not necessarily floating point) values. 2. Perform a 2D non-maximal suppression using the known approximate radius of each paw pad (or toe). This should give you the maximal positions without having multiple candidates which are close together. Just to clarify, the radius of the mask in step 1 should also be similar to the radius used in step 2. This radius could be selectable, or the vet could explicitly measure it beforehand (it will vary with age/breed/etc). Some of the solutions suggested (mean shift, neural nets, and so on) probably will work to some degree, but are overly complicated and probably not ideal.