The OCR
Optical Character Recognition or Optical Character Recognition (OCR) is the electronic or mechanical conversion of typed, handwritten or printed text images into machine-encoded text, whether from a scanned document, a still photo (e.g. text on signs and posters in a panoramic photo) or subtitle text superimposed on an image (e.g. from a television broadcast).
Widely used as a form of data entry from printed paper data records - whether passport documents, invoices, bank statements, computer receipts, business cards, mail, static data printouts, or any suitable documentation - it is a common method of digitising printed text so that it can be edited electronically, searched, stored more compactly, viewed online, and used in automated processes such as cognitive computing, machine translation, text-to-speech (extract), key data and text mining. OCR is a field of research in pattern recognition, artificial intelligence and computer vision.
Early versions had to be trained with images of each character and worked on one character at a time. Advanced systems capable of producing a high degree of recognition accuracy for most characters are now common, with support for a variety of input digital image file formats. Some systems are able to reproduce formatted output that closely approximates the original page, including images, columns and other non-textual components.
The first optical character recognition can be traced back to technologies involving telegraphy and the creation of reading devices for the blind. In 1914, Emanuel Goldberg developed a machine that read characters and converted them into standard telegraphic code. At the same time, Edmund Fournier d'Albe developed the optophone, a portable scanner that, when moved over a printed page, produced tones that corresponded to specific letters or characters.
In the late 1920s and 1930s, Emanuel Goldberg developed what he called a 'statistical machine' for searching microfilm archives using an optical code recognition system. In 1931, he was granted US patent number 1,838,389 for the invention. The patent was acquired by IBM.
