OCR and OCR Technology
OCR’s full form is Optical Character Recognition. OCR can be defined as software that is used for converting the pictures containing text into digital text that can be edited on a computer. It uses a certain device that reads the characters of the document and then converts them into digital code, understandable by a computer. It comprises various components that work together in order to yield the final result. The components include pattern identification, artificial intelligence, and machine vision.
The Principal of OCR Technology
Optical Character Recognition algorithm is the systems are the most advanced and that similar to ABBYY FineReader OCR are concentrated on duplicating the natural or “ beast-suchlike” recognition. In the heart of these systems lies these three abecedarian principles Integrity, Decisiveness, and Rigidity.
The principle of integrity says that the observed object always must be considered as a “ whole” conforming to numerous interrelated corridors.
The principle of decisiveness supposes that any interpretation of the data always must serve some purpose. The OCR specialists are to see the advantages of an OCR operation lifted on the IPA principles.
These principles endow the program with the maximum in flexibility and intelligence, bringing it as near as possible to mortal recognition.
Applications of OCR
The application of OCR can be seen in two systems namely matrix matching and feature extraction. Among the two
systems matrix matching is considered to be more simple and limited when compared to the other.
(a) Matrix Matching
This is also known as pattern matching. This system already contains a collection of bitmaps stored in it. Whenever a character is encountered in the document, that will be compared with the existing bitmaps. If a match is found then that will be taken as a plain text character. But the limitation of this system is that it can be used for characters with fonts and sizes that are available in its collection.
(b) Feature Extraction
This system is also called as Intelligent Character Recognition (ICR) (or) topological feature analysis. This type of OCR will not contain any set of bitmaps (or) characters. It carries out its search on the common elements like open spaces, closed
forms, lines, diagonals, etc.
The process of OCR is mostly seen in supermarkets and shopping malls when the tags are scanned in order to retrieve the data present on them.
- In all airports, for passport recognition and information extraction
- The Traffic sign recognition
- Extracting the business card information into a contact list
- The Automatic number plate recognition
- Make the electronic images of printed documents searchable, ex: Google Books
- Converting the handwriting in real-time to control a computer (pen computing)
- More quickly make textual versions of the printed documents, e.g. book scanning for Project Gutenberg
- Defeating the CAPTCHA anti-bot systems, though these are specifically designed and used to prevent the OCR.
- Assistive technology for the blind and visually impaired users
- Automatic insurance documents key information extraction
Advantages of OCR
- Improves data accuracy
- Increases the timeliness for processing the information
- Reduces the duplication of human effort involved in entering the data into the system.
Disadvantages of OCR
- OCR cannot be effectively used if the documents contain any strikeovers, erasures, and if the characters are not richly typed.