I'm trying to develop an image focusing algorithm for some test automation work. I've chosen to use AForge.net, since it seems like a nice mature .net friendly system.
Unfortunately, I can't seem to find information on building autofocus algorithms from scratch, so I've given it my best try:
take image. apply sobel edge detection filter, which generates a greyscale edge outline. generate a histogram and save the standard dev. move camera one step closer to subject and take another picture. if the standard dev is smaller than previous one, we're getting more in focus. otherwise, we've past the optimal distance to be taking pictures.
is there a better way?
update: HUGE flaw in this, by the way. as I get past the optimal focus point, my "image in focus" value continues growing. you'd expect a parabolic-ish function looking at distance/focus-value, but in reality you get something that's more logarithmic
update 2: okay, so I went back to this and the current method we're exploring is given a few known edges (okay, so I know exactly what the objects in the picture are), I do a manual pixel intensity comparison. as the resulting graph gets steeper, I get more in focus. I'll post code once the core algorithm gets ported from matlab into c# (yeah, matlab.. :S)
update 3: yay final update. came back to this again. the final code looks like this:
step 1: get image from the list of images (I took a hundred photos through the focused point)
step 2: find an edge for the object I'm focusing (In my case its a rectangular object that's always in the same place, so I crop a HIGH and NARROW rectangle of one edge)
step 3: get the HorizontalIntensityStatistics (Aforge.net class) for that cropped image.
step 4: get the Histogram (gray, in my case)
step 5: find the derivative of the values of the histogram
step 6: when your slope is the largest, is when you're in the most focused point.