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How we made our OCR code more accurate
Discover how Pieces enhanced its optical character recognition (OCR) engine to improve accuracy, speed, and real-world application for software developers.
OCR is now widely used in applications such as document scanning, data entry automation, and text-to-speech technology for people with visual impairments. We use Tesseract as the primary OCR engine, which performs layout analysis before using LSTM (Long Short-Term Memory) trained on text-image pairs to predict the characters. To evaluate our modifications to the OCR pipeline, we use multiple sets of hand-crafted and generated datasets of image-text pairs.
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