Imagine a scenario where you are building a model that performs word transcription from the image of a document. The first step would be to identify the location of words within the image. Primarily, there are two ways of identifying words within an image:
- Using deep learning techniques such as CRAFT, EAST, and more
- Using OpenCV-based techniques
In this section, we will learn about how machine-printed words can be identified in a clean image without leveraging deep learning. As the contrast between the background and foreground is high, you do not need an overkill solution such as YOLO to identify the location of individual words. Using OpenCV is going to be especially handy in these scenarios because we can arrive at a solution with very limited computational resources and, consequently, even the inference time will be very small. The only drawback is that the accuracy may not be 100%, but that is also subject to how clean the scanned...
