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.

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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.

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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

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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.

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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.

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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.

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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.

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References

• Raspberry Pi Documentation
• Tesseract OCR GitHub
• Espeak Documentation
• ItsFOSS Raspberry Pi Projects

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License

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