What is the right (or a good) way to robustly filter for text like this? Is there a "standard" technique that can latch onto this kind of outline? I'm hoping to stick to image processing and basic heuristics, rather than more advanced discrimination like machine learning. on the right here is a feature that looks quite "text-y" after thresholding.įiltering "small" contours is also challenging, as there are valid small strokes in Chinese, as well as punctuation like full stops and commas. I have tried to filter the image with a Laplace Pyramid filter (based on this example), but it's hard to find a filter that homes on the white text without often blowing noise in the background into pure white too. Some backgrounds are very noisy, so there can be a lot of spurious edges too (this is a bit contrived, as no filtering is done, and the Canny aperture is too big, but the double edges are visible): OpenCV in python helps to process an image and apply various functions like resizing images, pixel manipulations, object detection, etc. A naive first attempt that just thresholded the image is not sufficient, as it (predictably) produces artifacts in areas of white background (eg under the first and second characters in this example).Įdge detection is also challenging, as you get a decent "inner edge" for the white-black edge, but you might or might not get an outer edge for the black-background boundary (if the background is dark), or you might only get a partial or unclosed outline. Compare OCR accuracy before and after applying our image processing routine. ![]() Discover how to apply thresholding, distance transforms, and morphological operations to clean up images. ![]() What I'd like to achieve is something like this that can be fed to OCR: Use OCR With the EasyOCR Library to Extract Text From an Image in OpenCV In this article, there are four key things that we need to do: We need to install and import our dependencies. In this tutorial, you will: Learn how basic image processing can dramatically improve the accuracy of Tesseract OCR. What I'd like to achieve is a "tidy" black-on-white image of the text.Įxample input, something like this, where the background is uncontrolled, and can also be as white as the text. The text in question is mostly in Chinese script (some numbers and Latin letters) of a known font (looks like SimHei), is white (ish) and has a black (ish) border, and occurs left-aligned at a constant location. The getTextSize function calculates and returns width and height of a text string. This project combines the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS) in Raspberry pi to enable user to hear the. #include "opencv2/imgproc.I have some video frames I'd like to extract some text from (for making softsubs from hardsubbed video for learning). Get Text Size using OpenCV OctoOpenCV 0 Comments 1170 Views OpenCV has various drawing functions to draw geometric shapes such as line, rectangle, circle and write text on images. ImageText.cpp #include "Imaging/imageText.h" Mat image Mat::zeros ( windowheight, windowwidth, CV8UC3 ) Then we proceed to draw crazy stuff. ![]() In this example, rng is a RNG element initialized with the value 0xFFFFFFFF. It was a PITA until I figured out that the import was messing up with my social life. We observe that first thing we do is creating a Random Number Generator object (RNG): RNG implements a random number generator. The code compiled and linked fine however I was facing one weirdy behaviour with the putText (some garbage into my image). My test code used only the putText sample above and I did included the imgproc.h just as I did into some of my oldcode. OpenCV in python helps to process an image and apply various functions like resizing image, pixel manipulations, object detection, etc. One nasty detail that I saw into my test code: pay attention into the import stament - it is not displayed into most examples and it needs to be the right import.
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