Special Document Processing Techniques Explained
To address the two major difficulties in document digitization, RolmOCR has adopted the following innovative solutions:
- handwriting recognition: The model mixes 5 million+ handwriting samples during training and uses dynamic stroke feature extraction technique. Tests show that the recognition accuracy of Chinese running script reaches 78%, which is better than the level of 65% of similar tools. Specially optimized to distinguish between numbers 0-9 and easily confused characters (e.g. "7″ and "1″).
- tilt compensation: Through the data enhancement strategy, the model has a built-in auto-correction module for 15 rotation angles (-30° to +30°). The processing flow is:
- Detecting document edges using SIFT features
- Applying Perspective Transformations for Geometric Correction
- Tilt-compensated inference in feature space
Measured recognition accuracy for 30° skewed documents remains above 92%
Users are advised to simply crop severely skewed documents first and ensure that the DPI is ≥300 for best results.
This answer comes from the articleRolmOCR: Document OCR Model for Recognizing Handwritten and Slanted CharactersThe
May not be reproduced without permission:AI productivity tools " What special optimizations does RolmOCR have for handling handwritten and skewed documents?
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