Fast empty page detection
What are faster alternative approaches for accurately detecting empty pages in scanned images?


OK, convert is universally known to be rather hungry for RAM and potentially rather slow (due to its internal image model handling). My guess is that if you don't use it but, for example, simply do your whole detection within a scripting language with an image processing library (e.g. Python3 with PIL), you'll be fast enough for this to be a viable approach, as you, as a nice addition, won't be constantly saving and loading images from disk, but keep them in RAM until you're done, which is orders of magnitude faster. 

I like the blurring approach; it has the potential of removing noise sufficiently well. But:

Why don't you simply 


threshold to convert to black&amp;white (might want to do that adaptively based on the average brightness)
erode by a few pixels, just enough to kill dust and noise, 
count the remaining black pixels, and
declare clear page based on a threshold?


Since punch holes and margins will be larger in black area than two words, I'd previously try to just exclude them with a simple static mask, if your raw material permits (i.e. if you're scanning shelves of filed documents, then all will have the punch holes in the same place), or by trying to "smartly" detect them (for example, look for circles in potential punch-hole places, diagonal lines in potential staple places and so on).