I recommend trying the Java OCR project on sourceforge.net. I originally developed it, and I have a blog posting on it. Since I put it up on sourceforge, its functionality been expanded and improved quite a bit through the great work of a volunteer researcher/developer. Give it a try, and if you don’t like it, … Read more
Well, I decided to workout myself on my question to solve the above problem. What I wanted is to implement a simple OCR using KNearest or SVM features in OpenCV. And below is what I did and how. (it is just for learning how to use KNearest for simple OCR purposes). 1) My first question … Read more
fix DPI (if needed) 300 DPI is minimum fix text size (e.g. 12 pt should be ok) try to fix text lines (deskew and dewarp text) try to fix illumination of image (e.g. no dark part of image) binarize and de-noise image There is no universal command line that would fit to all cases (sometimes … Read more
Here’s an idea. We break this problem up into several steps: Determine average rectangular contour area. We threshold then find contours and filter using the bounding rectangle area of the contour. The reason we do this is because of the observation that any typical character will only be so big whereas large noise will span … Read more
Here’s a simple approach using OpenCV and Pytesseract OCR. To perform OCR on an image, its important to preprocess the image. The idea is to obtain a processed image where the text to extract is in black with the background in white. To do this, we can convert to grayscale, apply a slight Gaussian blur, … Read more
tesseract-4.0.0a supports below psm. If you want to have single character recognition, set psm = 10. And if your text consists of numbers only, you can set tessedit_char_whitelist=0123456789. Page segmentation modes: 0 Orientation and script detection (OSD) only. 1 Automatic page segmentation with OSD. 2 Automatic page segmentation, but no OSD, or OCR. 3 Fully … Read more