We'll start by converting the image to grayscale and applying thresholding to enhance the contrast between the text and the page background. Then, we'll use OpenCV functions to detect the lines of text and sort them by their position on the page. From there, we'll zoom in on each line and repeat the process to detect individual words. Finally, we'll store the words in an array along with their corresponding coordinates, making it easy to display any word on the page by selecting the corresponding item in the array.
Whether you're working on a digital library project or just want to extract text from scanned documents, this tutorial will give you the tools you need to succeed. So join us as we explore the exciting world of word segmentation with Python and OpenCV!
You can find the link for the tutorial here.
You can find the link for the Video tutorial here.
You can find more cool Tensorflow projects and tutorials in this playlist
Enjoy
Eran
🚀 Want to get started with Computer Vision or take your skills to the next level ?
If you’re just beginning, I recommend this step-by-step course designed to introduce you to the foundations of Computer Vision - Complete Computer Vision Bootcamp With PyTorch & TensorFlow
If you’re already experienced and looking for more advanced techniques, check out this deep-dive course - Modern Computer Vision GPT, PyTorch, Keras, OpenCV4
Before we continue , I actually recommend this book for deep learning based on Tensorflow and Keras :
If you have any suggestions about papers, feel free to mail me :)