OCR, Optical Character Recognition is also known as text recognition. It is a combination of hardware and software used to convert documents to texts that can be read by machines. It merely involves helping computers to identify characters and words in scanned documents containing words, letters, or images. The texts of the documents are examined, and code is produced, which is used for data processing. The hardware used may include an optical scanner or a circuit board that is used for copying or reading the text. The software is usually used for more advanced analytical functions. The software can take the whole process a step further by using artificial intelligence, AI to carry out more complex, intelligent character recognition, which includes identifying handwriting MS, and languages. OCR is predominantly used to convert legal or historical documents to format like they were initially created with a word processor. This means some alterations or corrections can then be done on the document. Also, it is now possible to search for words and phrases within the document.
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History
Early forms of text recognition were probably first seen in the early 20th century, where devices used by the blind for reading were invented. These devices could read and process characters in a document and provide a telegraph code. The optophone, which was a similar device capable of giving of specific tones for specific characters when the scanned characters were transferred to a printed page, was also invented by Edmund Fournier d’Albe. Emanuel Goldberg obtained a patent for his OCR invention between the 1920s and 1930s, called the statistical machine. It was used for searching microfilm archives. The OCR technology can now be used on smartphones having OCR Artificial intelligence.
Types of OCR
There are different types of OCR. They are very similar. One kind is intelligent character recognition, which involves machine learning and is well suited for converting handwritten documents by processing them character by character. Another is intelligent word recognition which targets handwritten or cursive text. It is of particular usefulness for languages in which the glyphs are not separated in the script. Optical word recognition identifies the characters one word at a time, using the spaces as a break between the words.
What does OCR entail?
First, the document is copied using a scanner. The physical form of all the pages of the document must be captured using the optical scanner. Afterward, the software translates the result of the copying into a black and white or a colored version. This is then analyzed for dark and light areas. The dark areas are for the characters, while the light areas are for spaces. The characters are observed singly and in groups. The characters may be alphabets or numbers. There are two algorithms used in identifying the characters. The first is the Feature detection in which involves the identification of the characteristics that are commonly done to alphabets. Another one is the pattern recognition in which the OCR system receives examples of texts in different fonts which are used to compare and identify the characters in the document. The next step is to convert the resulting file to ASCII code, which is used for making simple to complex adjustments on the document.
After deskewing, which helps to align the documents to the framework being worked with (It involves tilting or rotating the scanned document as required), a process of despeckling to remove spots and smoothen the edges follows. Others include line and word analysis, layout analysis, line removal, character isolation, and script recognition, among others.
Cuneiform and Tesseract are software used in character recognition, which recognizes the characters using a two-pass approach. For post-processing, there is a limit to the kind of characters that can be identified based upon the process by the lexicon in use. For example, using an English dictionary would probably prevent identification of “ã” or “ẞ” which are non- English characters. There is also a need for understanding the grammar of the language in which the document was created. This provides better accuracy. Here Copy Blogger has some useful tips on this point where grammar is the main theme of the sentence.
What can OCR be used for?
It can be used for extracting, promoting and automating data entry; making searchable formats of archives of books, magazines, journals, phone books and many more; adding valuable documents which have been signed and sealed to an electronic database; sorting of letters intended for mail delivery; converting documents into texts that can be read aloud to visually impaired or blind people; making scanned copies of documents so that they can be edited using word processors; creating an index of print materials on search engines; depositing checks electronically as against using a teller; and translation of words in a document into another language.
Advantages of OCR
OCR is a solution to many data processing problems, and although it involves complex processes, the usefulness of this technique cannot be overemphasized. Before the advent of OCR, any document for which a soft copy was needed had to be recreated digitally by hands. This was a very tiring process, and there was the issue of going through stress to find the exact characters in the original document, particularly for mathematical documents. It has afforded us minimal errors and effort and more time to do other things. The documents produced can have some keywords highlighted, can be compressed into a ZIP file, attached to an email or uploaded to a website.
OCR moves the paradigm from just taking images of documents to making them editable and searchable. Let HP scanning software make you more efficient but let OCR blow your mind giving you more value for your time and making your documents more useful in providing help.
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