First, I agree with the many others who have said that this is the wrong approach to the problem (and I have to wonder if this is what you were posting about last week).

Second, it might have been helpful to link to the code you're cribbing, since there's a better description there of how this technique works.

Third, I wonder about the utility of looking at the mean or standard deviation of an image's resulting vector. Imagine an image that is half black and half white and another that has the halves reversed. They're as different as night and day, but they have the same mean and standard deviation. If you had so many images that doing all the comparisons becomes a chore, narrowing your search using these values might be useful (or it might not), but you don't seem to have that many.

Finally, you might want to look at earlier nodes dealing with image recognition, such as Comparing images.