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I guess Python isn't so bad after all...

Not wanting to hassle with learning OpenCV and fighting with an edit-compile-execute environment, I decided to use my OpenCV project as an excuse to play around with Python.

I'm still a serious beginner, but I'm beginning to understand why it gets the use it does.

Anyhow, it only took a couple of days to integrate Tesseract OCR, PIL, and OpenCV such that I could open multi-frame TIFF images, perform some basic feature detection, and then use the output of feature detection to focus on a specific region for OCR.

I will admit to having a few false starts.  The first was that I used an older (C++) tutorial that was using some deprecated features of OpenCV and ignoring some other features.  For example, the tutorial was using Hough Line detection to find squares on a printed page.  In order to get to that point there was thresholding, dilating, eroding, inversion, flood filling and so on.  Even then I wasn't getting the correct results.

When I started over, I was using the old SWIG based interface instead of the newer stuff in the cv2 namespace.  Having used the newer stuff I've got to say it's much easier, especially when you need to move back and forth between OpenCV and PIL -- both libraries understand Numpy arrays.
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