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Visual Read Assist

Visual Read Assist is an innovative project designed to aid individuals with visual impairments. The device captures images, converts the text into machine-readable format using OCR (Optical Character Recognition), and reads the text aloud using text-to-speech technology. By leveraging the Raspberry Pi and other hardware components, this project aims to provide a low-cost and portable solution for visually impaired individuals to access and understand textual information independently.

Features

  • Image Capture: Utilizes the Raspberry Pi camera to capture high-quality images.
  • Optical Character Recognition (OCR): Converts captured images into machine-readable text using tesseract.
  • Text-to-Speech Conversion: Reads out the extracted text in real-time using espeak.
  • Audio Feedback: Provides audio cues for user interaction, such as Clicking picture and Picture clicked.
  • Portable and Low-Cost: Designed to be affordable and easy to use.

Components

Hardware Requirements

  • Raspberry Pi 4B+
  • 5MP Pi Camera
  • Speakers or Headphones
  • Power Supply
  • Push Button
  • Raspberry Pi Case

Software Requirements

  • Python 3
  • Raspbian OS
  • Required Libraries:
    • subprocess
    • pytesseract
    • aplay
    • PIL (Pillow)
    • espeak
    • libcamera-still
    • tesseract-ocr

Installation

1. Hardware Setup

  • Attach the Pi Camera to the Raspberry Pi’s camera slot.
  • Connect speakers or headphones for audio output.
  • Ensure the Raspberry Pi is powered on and connected to the internet.

2. Software Installation

  • Update and install the required packages: 
    sudo apt-get update
sudo apt-get install espeak tesseract-ocr libcamera-dev python3-pip
pip install pytesseract pillow
  • Verify the installation of Tesseract OCR: 
    tesseract --version

Ensure it displays the installed version without errors.

Usage

Step 1: Capture an Image

Run the click_image.py script to capture an image:

   python3 click_image.py
  • The program announces "Clicking picture" via audio.
  • Captures an image using the Raspberry Pi camera and saves it as test_image.jpg.
  • Announces "Picture clicked" once the image is saved.

Step 2: Extract Text and Convert to Speech

Run the image_to_text_speech.py script to process the captured image:

   python3 image_to_text_speech.py

  • The program reads the captured image (test_image.jpg by default).

  • Extracts text using Tesseract OCR.

  • Reads the extracted text aloud using espeak.

  • Prints the text in the terminal for reference.

Project Workflow

1.Image Capture :

  • Captures an image using the Raspberry Pi camera.
  • Provides audio feedback to indicate the image capture process.

Text Extraction:

  • Converts the captured image into text using OCR (Tesseract).

Text-to-Speech Conversion:

  • Synthesizes the extracted text into real-time audio feedback.

File Structure

  • click_image.py: Captures an image using the Raspberry Pi camera and provides audio cues during the process.
  • image_to_text_speech.py: Processes the captured image to extract text and convert it to speech.
  • test_image.jpg: The default filename for the captured image.
  • Dependencies:
    • pytesseract: For OCR functionality.
    • espeak: For text-to-speech conversion.
    • libcamera-still: For image capture.

Future Enhancements

  • Add support for multiple languages and handwriting recognition in OCR.

  • Enable users to select voices and adjust speech rates in text-to-speech.

  • Integrate with wearable devices, such as smart glasses, for hands-free operation.

  • Improve OCR performance using advanced AI and machine learning models.

References

License

This project is open-source and available under the MIT License.