Hi, I'm trying to use opencv to process text images before sending them to OCR. This involves binarizing the images, but because they vary greatly (from very dark to very faint), I need an adaptive thresholding method. I tried Otsu but id doesn't give the desired result. This is my original image:
...and this is what its like after Otsu thresholding:
...Otsu calculates a threshold of 238 for this image, but if I experiment manually, I find that that a threshold of 222 produces a better result as follows:
If I try adaptiveThreshold, the best I get is (with a block size of 17 and a C of 6) as follows:
...but this is still not as good as the 222 image. Can anyone suggest a programmatic way of coming up with an optimal threshold value? ....or some other adaptive method which might give me better results?
Any help would be much appreciated Thanks Jim
