Raisoni College of EngineeringAn Autonomous Institution under UGC Act 1965 |Accredited by NBA & NAAC ‘A’ Grade

DEPARTMENT OF ELECTRONICS AND TELECOMMUNICATION ENGINEERING

Session: 2016-2017

Semester/Branch/Section: –VII / ETC – CName of Subject:

Optical Communication

TAE- 2

Report On

Optical Character Recognition

Submitted by:

Akash Shahu (Roll No. 26)

Ashish Pandey (Roll No. 30)

Submitted To:

Prof. K. Jajulwar

E&TC Department, G.H.R.C.E.

Introduction:

Optical character recognition (optical character reader, OCR) is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example from a television broadcast). It is widely used as a form of data entry from printed paper data records, whether passport documents, invoices, bank statements, computerised receipts, business cards, mail, printouts of static-data, or any suitable documentation. It is a common method of digitising printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining. OCR is a field of research in pattern recognition, artificial intelligence and computer vision.Early versions needed to be trained with images of each character, and worked on one font at a time. Advanced systems capable of producing a high degree of recognition accuracy for most fonts are now common, and with support for a variety of digital image file format inputs.[2] Some systems are capable of reproducing formatted output that closely approximates the original page including images, columns, and other non-textual components.

Description:

Optical Character Recognition software does is optically recognize and represent each character in a scanned document, or, in other words, it translates an image of each character in a scanned document into an electronically designated character.

Character recognition process is very complex and requires that the OCR program matches each image letter to an electronic version that corresponds to it. The program has to recognize the font that is used in order to be able to recreate the document. In many cases the scanned copies of a document are of low quality, blurred, with unrecognizable characters, especially if the original paper copy was of poor quality, crumpled, faded, etc. In these cases it is really difficult for the OCR software to perform accurately and that’s when errors occur.

Until now they haven’t invented a completely error-free OCR software. However, advancements are continually made in this direction. Today we have

many professional OCR tools on the market that can convert scanned documents surprisingly well. One of them is the professional version of Able2Extract that includes advanced OCR capabilities and gives its users an opportunity to quickly overcome issues that come with image PDFs.

OCR is optical character recognition, a software tool that allows you to convert scanned documents into text searchable files. It is now increasingly common for documents to be scanned so that they can be conveniently viewed and shared via electronic means. However a scan is merely an image capture of the original document, so it cannot be edited or searched through in any way. This results in a decrease in efficiency since employees now have to manually correct or search through multiple pages. OCR solves this problem by making the document text searchable.

Types of OCR:

Optical character recognition (OCR) – targets typewritten text, one glyph or character at a time.

Optical word recognition – targets typewritten text, one word at a time (for languages that use a space as a word divider). (Usually just called "OCR".)

Intelligent character recognition (ICR) – also targets handwritten printscript or cursive text one glyph or character at a time, usually involving machine learning.

Intelligent word recognition (IWR) – also targets handwritten printscript or cursive text, one word at a time. This is especially useful for languages where glyphs are not separated in cursive script.

OCR is generally an "offline" process, which analyses a static document. Handwriting movement analysis can be used as input to handwriting recognition. Instead of merely using the shapes of glyphs and words, this technique is able to capture motions, such as the order in which segments are drawn, the direction, and the pattern of putting the pen down and lifting it. This additional information can make the end-to-end process more accurate. This technology is also known as "on-line character recognition", "dynamic character recognition", "real-time character recognition", and "intelligent character recognition".

PowerPoint Presentation onOptical Character Recognition