Welcome to the Braille Image Processing assignment for the Computer Vision course! In this assignment, you will be working with Braille images to extract the dots and then implement an algorithm to translate the Braille patterns into English. The focus is on using classical computer vision methods with OpenCV; neural networks are not allowed for this assignment.
You will be provided with two Braille images: braille1.jpg and braille2.jpg. Your goal is to develop a solution that accurately extracts the dots from these images and translates them into English characters.
- Clone this repository to your local machine:
git clone https://github.com/mshamrai-teaching/image-processing-braille-*your-name*- Navigate to the project directory:
cd image-processing-braille-*your-name*- Familiarize yourself with the provided Braille images:
- braille1.jpg
- braille2.jpg
- Tools: Use classical computer vision techniques with OpenCV.
- Files:
- braille1.jpg: First Braille image for processing.
- braille2.jpg: Second Braille image for processing.
- Restrictions: Neural networks are not allowed for this assignment.
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Image Preprocessing:
- Consider converting the images to grayscale.
- Explore thresholding techniques to enhance dot visibility.
-
Dot Extraction:
- Investigate contour detection to identify dot locations.
- Morphological operations might be useful in separating dots.
-
Translation to English:
- Create a mapping between Braille patterns and English characters.
- Implement a mechanism to interpret the dots and form English characters.
To submit your solution create pull request to the main branch.
Ensure your final submission includes:
- Source code (braille_processing.py\.ipynb or similar).
- Processed images (braille_processed1.jpg and braille_processed1.jpg or similar).
- A brief report (report.md or similar) explaining your approach and any challenges faced.
Good luck, and enjoy exploring the world of image stitching! If you have any questions, feel free to reach out.