How do I choose between Tesseract and OpenCV?
I recently came across Tesseract and OpenCV. It looks like Tesseract is a full-fledged OCR engine and OpenCV can be used as a framework to create an OCR application/service.
I tried using Tesseract on some of my images and its accuracy seems decent. Later, I came across a very simple tutorial on using OpenCV to perform OCR using Python and was impressed. In a few minutes, I finished training the system and its accuracy was good. But of course, taking this approach means I need to train my system extensively using a large training set.
My specific questions are the following:
- How does one choose between Tesseract and using OpenCV to build a custom OCR app?
- There are training datasets available for Tesseract for different languages. Does OpenCV have something similar so that I don't have to start ground up to achieve OCR?
- Which one is better for a wanna-be commercial application?
Any suggestions?
Answer
Tesseract is an OCR engine. It's used, worked on and funded by Google specifically to read text from images, perform basic document segmentation and operate on specific image inputs (a single word, line, paragraph, page, limited dictionaries, etc.).
OpenCV, on the other hand, is a computer vision library that includes features that let you perform some feature extraction and data classification. You can create a simple letter segmenter and classifier that performs basic OCR, but it is not a very good OCR engine (I've made one in Python before from scratch. It's really inaccurate for input that deviates from your training data).
If you want to get a basic understanding of how hard OCR is, try OpenCV. Tesseract is for real OCR.