An OCR tool must be able to recognize text however it is present on a page. One of the most immediate issues is that there is no universally consistent scanned document - a book, a legal document, a poster, and images of text may contain writing in many different forms, shapes, and sizes. When documents are scanned or otherwise converted into searchable PDFs, there are numerous challenges that must be overcome to turn the original files into data that can be used to train a Machine Learning model.
PDF EXPERT TEXT RECOGNITION PDF
What are the Challenges of Converting PDF to Text? In the early days of OCR, this technology was quite primitive and required the use of a special font set in order to work, but modern OCR technology is no longer limited to this and is even capable of recognizing handwriting in addition to digital font sets. As a result, you get actionable data from an otherwise non usable raw format. OCR works by analyzing the patterns of light and dark pixels that make up the defined characteristics of each character and then applies these patterns to known rulesets in order to identify each individual character in a document. PDF text recognition utilizes OCR technology to identify elements (images, graphs) & text characters in a scanned document. Read on to learn how this technology works and why it is useful. Rather than having to manually transcribe a PDF document, instead OCR ( optical character recognition ) technology is used to automatically identify text elements and convert them into usable text that can be searched and copied. PDF text recognition can automatically recognize and extract text from a PDF document and present it in a readily available text format.
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