- To build and evaluate an optical character recognition system that can process scanned book pages and turn them into text.
The figures below indicate accuracy/performance using nearest neighbour and PCA based approach - Each page decreases in quality with added noise.
| Noise value 0 - 98% accuracy | Noise value 0.1 - 98% accuracy | Noise value 0.2 - 92% accuracy |
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| Noise value 0.3 - 78% accuracy | Noise value 0.4 - 63% accuracy | Noise value 0.5 - 51% accuracy |
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Ensure you are in the correct directory then run:
pip install -r requirements.txt
Followed by:
run_evaluate.sh
The code should print out the percentage of correctly classified characters for each page.