OCR Full Form

OCR stands for optical character recognition. The full form of OCR in computer language is also known as an optical character reader (OCR) or text recognition. Its purpose is to convert scanned paper documents or digital camera photos of documents into readable, editable, and searchable data. When trying to digitise historic newspapers in the early 1990s, OCR technology became popular. Technology has progressed substantially since then. Nowadays, solutions provide OCR accuracy that is close to flawless. Complex Document-based operations are automated using advanced approaches such as Zonal OCR.

In this article, we will discuss OCR full form, OCR full form in computer and different techniques of OCR. We will also learn what is the full form of OCR in computer.

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A scanned page of a real document can be read on the screen, but to the computer, it is nothing more than a series of black and white dots. OCR was created to allow a computer to read a scanned document and make a soft copy. OCR scans the text of a scanned document and converts the characters into code that makes the text machine-readable, allowing it to be converted into an electronic format or soft copy that users can edit, format, search, and read, much like a document prepared with a word processor.

It uses the optical qualities of words and characters printed on a scanned page or document to help computers recognise words and characters on a scanned page or digital pictures of actual printed or handwritten materials.

A device that turns physical documents into machine-readable text is known as an optical character recognition (OCR) device. OCR hardware (such as an optical scanner or a circuit board) copies and scans text, while the software handles advanced processing. Artificial intelligence can also be used to apply advanced methods of intelligent character recognition (ICR), such as the capacity to recognise language or handwriting style. We will discuss in detail what is full form of OCR.

OCR Full Form in Computer

OCR stands for in computer is "Optical Character Recognition."OCR is a text recognition system that recognises text in digital images. OCR software locates and recognises characters such as letters, numbers, and symbols in a digital image. Some OCR software will merely export the text, while others will transform the characters to editable text in the image itself. Advanced OCR software can output the text's size and formatting, as well as the text's placement on a page.

Although OCR technology was created to recognise printed text, it may also be used to recognise and verify handwritten content. Postal services, such as the USPS, employ OCR software to handle mail and shipments automatically based on the address.

OCR Full Form in Banking

In banking, OCR stands for  Official Cash Rate. It's the interest rate that the Reserve Bank sets to achieve the dual mandate outlined in the Monetary Policy Committee's Remit.

What is OCR Used For?

Converting printed paper documents into machine-readable text documents is probably the most well-known use case for OCR. Following OCR processing, the text of a scanned.

paper document can be modified using word processors such as:

• Microsoft Word

• Google Docs

Prior to the development of OCR technology, the only way to digitise printed paper documents was to manually retype the text. Not only was this time-consuming, but it was also riddled with inaccuracies and typing.

Many well-known systems and services in our daily lives rely on OCR as a "hidden" technology. Data input automation, indexing documents for search engines, automatic number plate recognition, and assisting blind and visually impaired people are some of the less well-known, but equally significant, applications of OCR technology.

OCR technology has proven to be quite helpful in digitising old newspapers and texts, which have now been turned into fully searchable versions, making it much quicker and faster to access those earlier writings.

Do Banks use Optical Character Recognition?

The bank is one of the entities that use OCR the most in today's fast-paced environment. In the banking industry, document digitisation is quite useful. OCR technology is used by several institutions to improve transaction security and risk management.

Many clients' crucial handwritten guarantee documents, such as their loan documents, may be scanned using OCR software at banks. Additionally, the usage of facial recognition software in conjunction with OCR is noteworthy since it provides two-layer security at ATMs.

Different Technique of OCR

Let's look at three processes in the optical character recognition process: picture preprocessing, character recognition, and output post-processing.

Pre- Processing

To improve the possibilities of successful recognition, OCR software frequently preprocesses images. The goal of picture preprocessing is to make the image data better. As a result, undesirable distortions are reduced, while certain visual qualities are improved. Both of these things are necessary for further processing.

Character Recognition

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It's crucial to grasp feature extraction before moving on to character recognition. When an algorithm's input data is too vast to be processed, just a subset of characteristics is chosen. The features were chosen are expected to be the most important. The ones that are thought to be redundant are eliminated. By using the reduced set of data instead of the initial large one, the performance will be better.

The algorithm must detect specific areas or shapes of a digitised picture or video stream, this is critical for the OCR process.

Post-Processing

Another mistake correcting technique that ensures OCR accuracy is post-processing. If the output is limited by a vocabulary, the accuracy can be enhanced even more. As a result, the algorithm can fall back on a list of words that are allowed to appear on the scanned page.

How OCR Works?

• The document's physical shape is processed by the scanner.

• The software analyses the structure of the document after it has been scanned and converts it to a coloured (black and white) version.

• The document is scanned and analysed for light and dark areas.

• Characters are detected in dark areas, whereas the backdrop is distinguished in bright parts.

• The dark portions are examined further to determine whether they contain letters or numeric digits. The lines are broken down into words, and the words are broken down into characters.OCR attempts to determine if the dark areas represent a particular letter or number.

Once the characters have been identified, they are translated into an ASCII code that computer systems may utilise to perform further manipulations, resulting in the recognised text being shown to us.

OCR software uses a variety of methodologies, but in general, it analyses one character, word, or block of text at a time and then uses one of two algorithms to identify characters.

1) Pattern recognition: OCR software is created by feeding it examples of text in various fonts and formats, allowing it to recognise the shape or pattern of characters and accurately identify them.

2) Feature detection: OCR programmes use the feature of a character or a number in this technique. The number of angled lines, crossing lines, or curves in a character are examples of characteristics. For example, the letter 'A' could be recorded as two lines united at one end and connected in the middle by a horizontal line.

When a character is recognised, it is transformed into an ASCII code that computer systems can utilise to perform additional operations. Before saving a document for future use, users should rectify basic errors, proofread it, and double-check that complicated layouts were handled correctly.

Optical Character Recognition Use Cases

OCR can be used for a variety of applications, which are given below:

• Scanning printed documents into editable formats for word processors such as Microsoft Word or Google Docs.

• Indexing print material for search engines.

• Automating data entry, extraction and processing.

• Documents are deciphered into text that may be read aloud to visually impaired or blind people.

• Archiving historical material into searchable formats, such as newspapers, periodicals, and phonebooks.

• Without the need for a bank teller, we can deposit checks electronically.

• Important, signed legal documents are entered into an electronic database.

• Using a camera or software to recognise text, such as licence plates.

• Sorting letters in preparation for delivery.

• Words within an image are translated into a specific language.

Conclusion:

We have discussed what is the full form of OCR. We can say that the main advantages of OCR technology are saved time, decreased errors and minimized effort. It also allows you to do things that physical copies can't, such as compressing data into ZIP files, highlighting keywords, incorporating them into a website, and attaching it to an email.

While taking images of documents enables them to be digitally archived, OCR provides the added functionality of being able to edit and search those documents.