OCR using OpenCV on Brainy Pi

Optical Character Recognition (OCR) is a powerful technology that has revolutionized the way we interact with printed text. With OCR, we can convert printed text into digital format, enabling easy editing, searching, and sharing. OpenCV, an open-source computer vision library, provides a comprehensive set of tools for image processing and pattern recognition, making it an excellent choice for OCR applications. In this blog post, we will explore how to use OCR using OpenCV on Brainy Pi , a powerful single-board computer designed for enterprises to build and deploy their industry ready applications. We will discuss the technical details of OCR, and how OpenCV can be used to perform character recognition on images captured using the Brainy Pi camera module. We will also provide code examples and demonstrations of practical OCR applications on the Brainy Pi platform.

Text Detection

We will use a Python script that uses computer vision and OCR to capture and read text from an image or video stream. The script consists of two files: ocr.py and ocrUtils.py.

ocr.py

The ocr.py file imports necessary libraries including OpenCV, pytesseract, numpy, ImageGrab, time, and ocrUtils. It defines a main function that does the following:

1. Initializes a camera object (using either a Raspberry Pi camera or a connected webcam).

2. Captures an image from the camera.

3. Uses ocrUtils to read text from the captured image using pytesseract.

4. Displays the captured image with text overlaid on it.

5. Prints the text

ocrUtils.py

The ocrUtils.py file contains a Python function readCharacters() that reads characters from an input image using the Tesseract OCR engine.

1. readCharacters()

   • Input

     1. img ([cv2.Mat]): Input Image

     2. draw (bool, optional): Should we draw characters in the image. Defaults to False.

   • Output

     1. text ([str]): Text output of OCR

     2. img ([cv2.Mat]): Output Image

Running Code for OCR using OpenCV on Brainy Pi

Before we can run the code, we need to install all the necessary dependencies and clone the code repository.

1. Clone the code repository:

   git clone https://github.com/brainypi/brainypi-opencv-examples.git
   cd text-detection

2. Install the dependencies:

   sudo apt install tessaract-ocr
   pip install -r requirements.txt

3. Running the Code

   python ocr.py

Input Image through Camera

Text Detection

Text Recognition

To exit out of the program, simply press q.

Conclusion

OCR using OpenCV and pytesseract is a powerful tool for text recognition in images and video streams. With the help of the code provided in this blog post, you can get started with text detection and recognition in your own projects.