Training machines to understand and record human languages is another significant step toward making artificial intelligence (AI) more human. Powered by deep learning, Tesseract OCR is one such AI engine that enables computers to capture and extract text from scanned documents. This article serves as a comprehensive guide to install, run, and implement Tesseract OCR with Python and OpenCV.

Let’s explore how Tesseract OCR enhances traditional optical character recognition services for building enterprise-grade AI solutions.

Getting Started With Tesseract OCR
Tesseract is an open-source Optical Character Recognition (OCR) engine originally initiated as a research paper by Hewlett Packard and later developed by Google. The latest version, Tesseract 4.0, is available under the Apache 2.0 license and can detect over 100 languages from images and videos.

Tesseract’s compatibility with several programming languages makes it an efficient tool for extracting text from large volumes of documents and images.

With Tesseract, providers of artificial intelligence development services are able to achieve optimum accuracy and efficiency with the following structural advantages-

a) Flexibility in Training
Tesseract is an example based system working on a set of rules that can be easily modified depending on the requirement.

b) Multiple output formats
The OCR engine supports various output formats including plain text, HTML, PDF, TSV, and XML.

c) A Layered Architecture
The first step begins with color sensing followed by converting the image into binary images. The third is the main step as it extracts the character outline and does OCR to further organize the text into lines and regions. Text recognition is then possible with the adaptive classifier that needs to be trained for producing effective results as shown below.

The OCR engine has its origins in OCRopus’ Python-based LSTM (Long Short Term Memory) which is a class of Recurrent Neural Network (RNN). LSTMs are highly efficient at learning from a long sequence of words and predicting the next word. In the next section, we will decode how to install and run Tesseract OCR with Python and OpenCV.

nstalling Tesseract OCR on Windows
Though Tesseract can be easily installed on various operating systems, for this post we will focus on Windows with the support of precompiled binaries. The first step is to download the version Tesseract 4.0 or above on your system and run Python-tesseract (PyTesseract) with the following command-

$ pip install pytesseract

Pytesseract is a wrapper for Tesseract OCR that recognizes text from all image types supported by Pillow and Leptonica imaging libraries. It requires Python 2.7 or Python 3.5+ along with PIL or Pillow fork. You can use the following pip to install Pillow, Pytesseract, and Imutils.

Learn more: Deploying Tesseract OCR With Python and OpenCV

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