Handwritten Digits and Optical Characters Recognition

2019

2317 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number F8614088619/2019©BEIESP DOI: 10.35940/ijeat.F8614.088619  Abstract: Optical character recognition (OCR) is a strategy to perceive character from optically checked and digitized pages. OCR plays an important role for Indian script research. The official language of the state Odisha is Odia. OCR face an incredible difficulties to recognize Odia language due to similar shape characters, their complex nature, the complicated way in which they combine form to compound character, use of Matra etc. Each character and numbers are passed through several modules like binarization, noise removal, segmentation, line segmentation, word segmentation, skeletonization, deskewing, thinning, thickening. The input picture is standardized to a size of 50 x 50 2D pictures. HMM is a stochastic process which has utilized in various applications for example speech recognition, Handwriting recognition, Gesture rec...

In the running world, there is growing demand for the software systems to recognize characters in computer system when information is scanned through paper documents as we know that we have number of newspapers and books which are in printed format related to different subjects. These days there is a huge demand in " storing the information available in these paper documents in to a computer storage disk and then later reusing this information by searching process ". One simple way to store information in these paper documents in to computer system is to first scan the documents and then store them as IMAGES. But to reuse this information it is very difficult to read the individual contents and searching the contents form these documents line-by-line and word-byword. The reason for this difficulty is the font characteristics of the characters in paper documents are different to font of the characters in computer system. As a result, computer is unable to recognize the characters while reading them. This concept of storing the contents of paper documents in computer storage place and then reading and searching the content is called DOCUMENT PROCESSING. Sometimes in this document processing we need to process the information that is related to languages other than the English in the world. For this document processing we need a software system called CHARCATER RECOGNITION SYSTEM. This process is also called DOCUMENT IMAGE ANALYSIS (DIA).

2020

1-2Student, Dept. of Computer Science and Engineering, MIT School of Engineering, MIT ADT University, Pune, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract Since olden times, the need for storing information in various ways has always been there. This was very useful until we felt the need to reuse this information again and again. In request to reuse these snippets of data, we had to read and search individual contents from different documents and then rewrite it again. Thus, there is an explicit need for automated softwares or programs in order to provide fast and accurate methods to revive the text from the longlasting images and documents.

2021

Optical Character Recognition (OCR), is that the process of conversion of image text or handwritten text into machine understandable form. Simply OCR means conversion of characters that is recognized and convert it into computer readable form. It is widely used as a kind of data entry from original paper data sources such as banking papers or consultation papers, whether passport documents, invoices, statement, receipts, card, mail or any number of printed records. It is a standard method of digitizing printed texts in order that they will be electronically edited, searched, and stored more compactly. OCR is the field of research in Pattern Recognition, Artificial Intelligence and Computer Vision. OCR is that the electronic translation of handwritten, type written or printed text into machine translated images. It is widely used to recognize and search text from documents or to publish the text on a website. This document represents review of Optical Character Recognition methods su...

International Journal of Advance Research In Science And Engineering (IJARSE), India, ISSN 2319-8346 (P), ISSN-2319-8354(E), Vol.3, Issue 7, Pages 261- 274, 2014

Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic conversion of scanned or photographed images of typewritten or printed text into machine-encoded/computer-readable text. It is widely used as a form of data entry from some sort of original paper data source, whether passport documents, invoices, bank statement, receipts, business card, mail, or any number of printed records. It is a common method of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as machine translation, text-to-speech, key data extraction and text mining. OCR is a field of research in pattern recognition, artificial intelligence and computer vision. Optical Character Recognition or OCR is the electronic translation of handwritten, typewritten or printed text into machine translated images. It is widely used to recognize and search text from electronic documents or to publish the text on a website [1]. A large number of research papers and reports have already been published on this topic. The paper presents introduction, major research work and applications of Optical Character Recognition in various fields. At the first introduction of OCR will be discussed and then some points will be stressed on the major research works that have made a great impact in character recognition. And finally the most important applications of OCR will be covered and then conclusion.

The project focus on the creation of OCR software for the off-line recognition of handwriting. OCR programs can recognize printed text with nearly perfect accuracy. The recognition of handwriting is harder due to the many different styles and inconsistent nature of handwriting. Handwritten text recognition (HTR) is an open field of research and a relevant problem that helps automatically process historical documents. In recent years great advances in deep learning and computer vision have allowed improvements on document and image processing including HTR. Handwritten text recognition plays an important role in the processing of vital information. Processing of digital files is cheaper than processing traditional paper files even though a lot of information is available on paper. The aim of an OCR software is to convert handwritten text into machine readable formats. Despite such advances in this field, little has been done to produce open-source projects that address this problem as well as methods that utilize graphical process units (GPUs) to speed up the training phase.

Optical Character Recognition by using Template Matching is a system which is useful to recognize the character or alphabets in the given text by comparing two images of the alphabet. The objectives of this system prototype are to develop a program for the Optical Character Recognition (OCR) system by using the Template Matching algorithm . This system has its own scopes which are using Template Matching as the algorithm that applied to recognize the characters, which are in both in capitals and in small (A – Z),and the numbers (0 -9) used with courier new font type, using bitmap image format with 240 x 240 image size and recognizing the alphabet by comparing between images which are already stored in our database is already . The purpose of this system prototype is to solve the problems of blind peoples who are not able to read , in recognizing the character which is before that it is difficult to recognize the character without using any techniques and Template Matching is as one of the solution to overcome the problem

Encyclopedia of Information Science and Technology, Third Edition, 2015

2015

Optical Character Recognition (OCR) is a system that provides a full alphanumeric recognition of printed or hand written characters by simply scanning the text image. OCR system interprets the printed or handwritten characters image and converts it into corresponding editable text document. The text image is divided into regions by isolating each line, then individual characters with spaces. After character extraction, the texture and topological features like corner points, features of different regions, ratio of character area and convex area of all characters of text image are calculated. Previously features of each uppercase and lowercase letter, digit, and symbols are stored as a template. Based on the texture and topological features, the system recognizes the exact character using feature matching between the extracted character and the template of all characters as a measure of similarity.

Vol. 19 No. 2 FEBRUARY 2021 International Journal of Computer Science and Information Security (IJCSIS), 2021

This paper provides a total overview of OCR. Optical character recognition is nothing but the ability of the computer to collect and decipher the handwritten inputs from documents, photos or any other devices. Over these many years, many researchers have been researching and paying attention on this topic and proposed many methods which can be solved. This research provides a historical view and the summarization of the research which done on this field.