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Optical Character Recognition System

2 big stars
Optical Character Recognition System screenshot
Name: Optical Character Recognition System
Works on: windowsWindows NT and above
Developer: Luigi Rosa
Version: 1
Last Updated: 24 Apr 2017
Release: 19 Nov 2012
Category: Others > Home and Education
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Optical Character Recognition System Tags

Optical Character Reader
details

Optical Character Recognition System Details

Works on: Windows 10 | Windows 8.1 | Windows 8 | Windows 7 | Windows XP | Windows 2000 | Windows 2003 | Windows 2008 | Windows 98 | Windows ME | Windows NT | Windows Vista | Windows 2012
SHA1 Hash: 03e6e3f3e271bf705e0845ab645e1521fb7ef937
Size: 66.86 KB
File Format: zip
Rating: 2.086956521 out of 5 based on 23 user ratings
Downloads: 182
License: Free
Optical Character Recognition System is a free software by Luigi Rosa and works on Windows 10, Windows 8.1, Windows 8, Windows 7, Windows XP, Windows 2000, Windows 2003, Windows 2008, Windows 98, Windows ME, Windows NT, Windows Vista, Windows 2012.
You can download Optical Character Recognition System which is 66.86 KB in size and belongs to the software category Home and Education.
Optical Character Recognition System was released on 2012-11-19 and last updated on our database on 2017-04-24 and is currently at version 1.
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features

Optical Character Recognition System Description

Optical character recognition (OCR) is the translation of optically scanned bitmaps of printed or written text characters into character codes, such as ASCII. This is an efficient way to turn hard-copy materials into data files that can be edited and otherwise manipulated on a computer. This is the technology long used by libraries and government agencies to make lengthy documents quickly available electronically. Advances in OCR technology have spurred its increasing use by enterprises. For many document-input tasks, OCR is the most cost-effective and speedy method available. And each year, the technology frees acres of storage space once given over to file cabinets and boxes full of paper documents. Before OCR can be used, the source material must be scanned using an optical scanner (and sometimes a specialized circuit board in the PC) to read in the page as a bitmap (a pattern of dots). Software to recognize the images is also required.Our software package proposes to solve the classification of isolated handwritten characters and digits of the UJI Pen Characters Data Set using Neural Networks. The data consists of samples of 26 characters and 10 digits written by 11 writers on a tablet PC. The characters (in standard UNIPEN format) are written both in upper and lower case and there is a whole two set of characters per writer. So the output should be in one of the 35 classes. The ultimate objective is building a writer independent model for each character.The selection of valuable features is crucial in character recognition, therefore a new and meaningful set of features, the Uniform Differential Normalized Coordinates (UDNC), introduced by C. Agell, is adopted. These features are shown to improve the recognition rate using simple classification algorithms so they are used to train a Neural Network and test its performance on UJI Pen Characters Data Set.Index Terms: Matlab, source, code, ocr, optical character recognition, scanned text, written text, ascii, isolated character.
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