Optical character recognition is a method of converting handwritten, typed or printed text in an image to the machine-encoded text that can later be edited, searched and used for further processing. In the following blogs, we will learn how to create an optical character recognition(OCR) pipeline using deep learning and computer vision.

CONTENTS

1. Optical Character Recognition: Introduction and its Applications
2. Optical Character Recognition Pipeline
3. Optical Character Recognition Pipeline: Text Detection
4. Efficient and Accurate Scene Text Detector (EAST)
5. Implementation of Efficient and Accurate Scene Text Detector (EAST)
6. Optical Character Recognition Pipeline: Text Recognition
7. CRNN model and CTC Problem Statement
8. Text Recognition Datasets
9. Creating a CRNN model to recognize text in an image (Part-1)
10. Creating a CRNN model to recognize text in an image (Part-2)

COURSES

Hey, here is the new course about optical character recognition using deep learning and OpenCV-Python. In this course you will learn, what is Optical Character Recognition. You will learn about a general OCR pipeline used by most industries. You will see different Image Pre-processing techniques used in OCR pipeline. Different Text Detection techniques used in OCR pipeline such as EAST and CTPN. Next, we will learn the different text recognition techniques used in OCR pipeline such as CRNN (CNN+RNN+CTC). And finally we will see the end-to-end implementation of a real-life OCR use case using Pytesseract. If you are interested go through course link provided by following banner:

Note: For more details on the Optical Character Recognition , please refer to the Mastering OCR using Deep Learning and OpenCV-Python course.