I am working on an application where I need to collect data from lots of regular people. I am looking for an efficient, reliable, inexpensive alternative to "Scantron" (used for machine-readable multiple-choice exams)<p>I am hoping to use a Mac laptop with a portable scanner (http://www.fujitsu.ca/products/scansnap/s300m/) that scans pages to PDF.<p>I have complete freedom for how the data forms are designed, ... and I am looking for reliable (free?/open source?) software that could capture the data from the (scanned) PDF and save it to a text file.<p>If anyone has any experience with something similar, I'd really appreciate hearing from you. Any other links or suggestions would be appreciated too.
You probably have to roll your own version if you want it. <a href="http://answers.yahoo.com/question/index?qid=20090421184939AAx9aCj" rel="nofollow">http://answers.yahoo.com/question/index?qid=20090421184939AA...</a><p>I haven't looked too far into this domain but I would imagine that it is not too difficult to do on a smallish scale.<p>On the actual form itself have some kind of scale and position marker in the top left and bottom right corners to give you orientation and scale of the scanned image. Then do some image analysis at predefined positions on the page. (of course you need to take into consideration the scale of the sheet and the orientation to make sure your offset vector is going in the right direction and distance per question.)<p>edit: this may be what you are looking for:<p><a href="http://www.cs.uwaterloo.ca/~a3seth/udai/OMRProj/" rel="nofollow">http://www.cs.uwaterloo.ca/~a3seth/udai/OMRProj/</a>
its not quite what you're looking for, i think, but i've heard good things about <a href="http://www.pdftoword.com/" rel="nofollow">http://www.pdftoword.com/</a>
Doing a little more online research, it seems like I am looking for a free/open-source solution for OMR (optical mark recognition) using a generic image scanner or PDF (instead of a specialized device that just scans OMR forms).<p>I wonder if there are computer/machine vision hackers who might know where to find (or put together) a good solution.