OCR optimization techniques

OCR (Optical Character Recognition) optimization techniques improve the accuracy and efficiency of converting images of text into editable, searchable data. These methods include enhancing image quality through noise reduction and contrast adjustment, training algorithms with diverse font and handwriting samples, and using language models to predict and correct errors. Additionally, segmenting text into manageable parts and leveraging contextual clues help improve recognition. Together, these techniques ensure the OCR system accurately captures important details, even from degraded or complex documents, enabling more reliable digital text extraction.