Optical Character Recognition with OpenCV, Tesseract, and Python

Learn how to successfully and confidently perform Optical Character Recognition (OCR) inside my new book, OCR with OpenCV, Tesseract, and Python.

Inside the book we focus on:

- Getting started with OCR
- Learning the basics of the Tesseract OCR engine
- Discovering how to improve OCR accuracy using Tesseract options and configurations
- Interfacing with Tesseract via the Python programming language
- Localizing and detecting text in images using both OpenCV and Tesseract
- Using OpenCV and image processing techniques to improve OCR accuracy
- Using machine learning to denoise our images for better OCR accuracy
- Document registration and alignment to build an invoice, receipt, and form scanning project
- Training our own custom deep learning OCR models with Keras and TensorFlow
- Solving Sudoku puzzles with OCR, OpenCV, and Keras/TensorFlow
- Automatic License/Number Plate Recognition (ANPR)
- Handwriting recognition
- Performing OCR in real-time video streams
- Utilizing GPUs for faster OCR inference
- Using OCR engines in the cloud (i.e., Google Vision API, Amazon Rekognition, etc.)
- Tips, suggestions, and best practices when performing OCR

You will get 35 chapters of expert instruction, hands on examples, and code you can download and extend. This is the fastest way to use OCR in your own projects.

Pick up your copy today!