Optical Character and Digit Recognition System (original) (raw)
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Handwritten Digits and Optical Characters Recognition
International Journal on Recent and Innovation Trends in Computing and Communication
The process of transcribing a language represented in its spatial form of graphical characters into its symbolic representation is called handwriting recognition. Each script has a collection of characters or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input characters or images before being analysed by various automated process systems. Recent research in image processing demonstrates the significance of image content retrieval. Optical character recognition (OCR) systems can extract text from photographs and transform that text to ASCII text. OCR is beneficial and essential in many applications, such as information retrieval systems and digital libraries.
An Overview and Applications of Optical Character Recognition
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.
Optical Text Recognition: Basic Procedures and Current State
2000
The survey of today's state of tools for optical text recognition is given in this scientific paper. Tools for processing handwritten symbols still did not enter in wide usage except in some specific cases such as hand-held computer. In the context of this scientific paper, given solutions were used in program "Handwritten Symbol Recognition". Today, on the other hand, tools for printed text recognition are already in wide usage. In the context of this scientific paper, tests of speed and accuracy of the recognition had been carried out for few today's popular commercial tools.
International Journal of Machine Learning and Computing, 2012
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. The paper presents a survey of applications of OCR in different fields and further presents the experimentation for three important applications such as Captcha, Institutional Repository and Optical Music Character Recognition. We make use of an enhanced image segmentation algorithm based on histogram equalization using genetic algorithms for optical character recognition. The paper will act as a good literature survey for researchers starting to work in the field of optical character recognition.
IRJET- OPTICAL CHARACTER AND DIGIT RECOGNITION SYSTEM
IRJET, 2020
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 long-lasting images and documents. Also, as we are advancing in this world full of technology, where new softwares are emerging, there is an increasing demand for softwares that recognize characters or words which can be converted into editable documents used wherever and whenever we want. As we surf the internet, we come across various facts, figures or data that we need, but cannot be replicated or edited since these documents are collected in the form of images. In our busy lives, we need everything instantly. Hence, the data being small or large, typing it can be time consuming. In such scenarios, the software like the Optical Character Recognition comes into play. In this research paper, we have proposed the system which detects text from images or documents and converts them into an editable format which is more efficient and less time consuming. We also have a developed a system that detects numbers which are obscure and displays them in an understandable format. We used OCR algorithms, python libraries and ML pre-processing concepts and we used it on datasets that give us significantly good outputs with an efficient and simple manner.
Optical Character Recognition (OCR) System
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).
Data Extraction from Images through OCR
IJRASET, 2021
The paperwork used in maintaining various types of documents in our daily lives is tiresome and inefficient, it consumes a lot of time and it is difficult to maintain and remember the concerned documents. This project provides a solution to these problems by introducing Optical Character Recognition Technology (OCR) which runs on Tesseract OCR Engine. The project specifically aims at increasing data accessibility, usability and improving customer experience by decreasing the time spent to process, save, and maintain user data. Another objective of this project is to nullify the human error, which is huge in manual handling of data records, the software used in the solution uses certain techniques to minimize these errors. Optical Character Recognition (OCR) is used for extracting texts and characters from an image. This helps us in maintaining our records and data digitally and securely. In this project we are using the Tesseract OCR Engine which has high accuracy rates for clean images. We have implemented a web version of OCR which runs on TesseractJS; other JavaScript frameworks are also used. The outcome of the project is that it is able successfully to extract text and characters from the provided image using Tesseract OCR Engine. It is observed that for the high resolution images the accuracy is above 90%. This web based application is useful for small businesses as they don't have to install any extra software, all it needs is a file to be uploaded on an online interface making them able to access remotely. It will also help students to save notes and documents online which will make their important documents easily accessible on the web. This whole process is time and memory efficient.
Digital Document Archiving System with Optical Character Recognition
2013
Computers are playing an important role in automation of various process and industries and Digital Data Archiving is one of them where in we tend to improve the working of office through some software process. Each Day numerous letters, visting cards and documents are received and generated in offices and then they are stored in files and folders in offices. To search any document takes a lot of time andthe things go more worse when we don’t remember the date or heading of this document / letter but just the sender’s name or just a line from the text of the document.. There is also chances of misplacement of these documents. So it is the need of the hour to built an application that will have capabilities to scan documents and store them in image format, extract the text out these images and store that text in database. What this will achieve is to allow an efficient and easy search of documents by just typing sender’s name or the company name.
A Hybrid approach for Optical Character Verification
International Journal for Scientific Research and Development, 2017
At present scenario, there is growing demand for the software system to recognize characters in a computer system when information is scanned through paper documents. This paper presents detailed review in the field of Optical Character Recognition. Various techniques are determined that have been proposed to realize the center of character recognition in an optical character recognition system. OCR (Optical Character Recognition) translates images of typewritten or handwritten characters into the electronically editable format and it preserves font properties. Where OCV (Optical Character Verification) is a hybrid approach of OCR and pattern matching. Different techniques for pre-processing and segmentation have been surveyed and discussed. Proposed methodology and the dataset are presented here. Intermediate results have shown in this paper.
Implementing a System for Recognizing Optical Characters
In the current paper we present a system of characters recognition by taking the photo of character with the identity of symbolic. In the proposed system we are going to make a scan in kind of optical for input character in order to be digitized. After that every character will be segmented and located and after that it will be obtained as a photo to be processed for normalization and even for reducing noise. After that it will be classified. Then from the obtained extraction we can find various techniques like weakness and strengths. Next step will be grouping the characters which identified in order to obtain the original string of symbols and we can apply the context in order to fix and detect false. The results show us that the system is working well and the recognition is really good. The system proposed in a program, developed in Matlab environment, which provides the ability to insert a character in an image. It is agree that making a machine to do what human can do is a dream, for example reading is one of the most important functions that humans are doing. However, this dream is becoming true day by day and researchers and working on this by many ways, where nowadays artificial intelligence is focusing on pattern recognition and in this field it is also focusing on the applications of character recognition and even many organizations and companies are designing systems for character recognition by many application and even that it is facing some challenges to make machines be able to read like humans and have the same capabilities. Recognizing characters is challenging some problems with the optical characters. Although, it is performed to be off line optical recognition for characters especially after completing the printing and writing, and to be online recognition to recognize characters as they have been drawn or written. Printed characters and even hand written characters could be recognized, but what we are always looking for is the performance where especially it is depending on the quality of files that been entered. Next step of challenging reviewed by many researchers is the online and the offline cursive writing. To get new ideas in the recognition of pattern, the classifying of characters could be tested, but where the experiments results are conducted on isolated characters, here the results are not necessary in case of immediately relevant to optical character recognition. Maybe more striking than the improvement of the accuracy and limit in methods of classification has been decreased in cost. The old devices of optical character recognition equipments were some optical hardware like the optical page reader of the company of IBM in order to read typed earning reports at the social security administration which cost more than two million dollars and some electronic and some high expensive scanners. Nowadays, the software of optical character recognition is often add on to scanner of desktop which is not costly. The main goal is to examine some details in examples of the false which committed by the proposed system. 2. PROPOSED SYSTEM The general technique is very simple to describe. The proposed optical character recognition system will contain some components and they are presented in figure 1. The install is illustrated, where to digitize the analog file by the optical scanner will be the first step in the system. After that the area which containing characters will be located and every symbol extracted by the process of segmentation. After that applying a preprocessing on the extracted symbols and then we are going to reduce the noise and eliminate it in order to make it easier the feature extraction to be prepared for the coming step. After that we are going to comparing the description of the classes of symbols which are gained by a phase of previous learning with the extracted features in order to find the identity of the symbol. Then to reconstruct the numbers and words of the original string we are going to use the contextual information.