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What is the most reliable and effective free OCR software or service that can accurately convert scanned documents and images to editable text files?
Tesseract, a popular open-source OCR engine, was originally developed by HP in the 1980s and was later acquired by Google in 2006.
Google Cloud Vision OCR can extract text from images with a accuracy rate of up to 99.9% when the input image is of high quality.
Adobe Acrobat Reader DC's OCR function uses a technology called "ClearScan" which can detect and correct distortions in scanned documents.
Online OCR tools like Free OCR and SimpleOCR use a combination of algorithms and machine learning models to improve their accuracy over time.
OCR technology is based on the concept of pattern recognition, where the software identifies and matches patterns of light and dark areas in an image to corresponding characters.
The accuracy of OCR software can be affected by the quality of the input image, with noise, blur, and low resolution reducing accuracy.
Some OCR tools, like i2OCR, support recognition of text in multiple languages, including non-Latin scripts like Chinese, Japanese, and Korean.
OCR software can be used for more than just converting scanned documents, it can also be used for data extraction, sentiment analysis, and content recognition.
The process of OCR involves several stages, including image pre-processing, feature extraction, and post-processing to correct errors.
Some free OCR tools, like Soda PDF, offer additional features like PDF merging, compressing, and editing, making them a more comprehensive solution for document management.
OCR technology has many applications beyond document scanning, including license plate recognition, facial recognition, and autonomous vehicles.
The accuracy of OCR software can be improved by using techniques like binarization, which converts grayscale images to binary black and white images.
OCR software can also be used to recognize handwriting, with some tools, like Google Cloud Vision OCR, offering high accuracy rates for handwriting recognition.
The development of OCR technology has been driven by the need to digitize large collections of documents, such as archives and libraries.
Some OCR tools, like Optiic, use a combination of OCR and artificial intelligence to recognize and correct errors, resulting in higher accuracy rates.
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