A Study on Optical Character Recognition Techniques (original) (raw)

A REVIEW: OPTICAL CHARACTER RECOGNITION

This paper presents detailed review in the field of Optical Character Recognition. Various techniques are determine that have been proposed to realize the center of character recognition in an optical character recognition system. Even though, sufficient studies and papers are describes the techniques for converting textual content from a paper document into machine readable form. Optical character recognition is a process where the computer understands automatically the image of handwritten script and transfer into classify character. This material use as a guide and update for readers working in the Character Recognition area. Selection of a relevant feature extraction method is probably the single most important factor in achieving high character recognition with much better accuracy in character recognition systems without any variation.

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.

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.

OPTICAL CHARACTER RECOGNITION: AN ENCOMPASSING REVIEW

Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. Basically, OCR technique converts images into editable format. This technique converts images in the form of documents such as we can edit, modify and store data more safely for longtime. This paper presents basic of OCR technique with its components such as pre-processing, Feature Extraction, Classification, post-processing etc. There are various techniques have been implemented for the recognition of character. This Review also discusses different ideas implemented earlier for recognition of a character. This paper may act as a supportive material for those who wish to know about OCR.

Optical Character Recognisation

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

A Survey on Optical Character Recognition System

2017

Optical Character Recognition (OCR) has been a topic of interest for many years. It is defined as the process of digitizing a document image into its constituent characters. Despite decades of intense research, developing OCR with capabilities comparable to that of human still remains an open challenge. Due to this challenging nature, researchers from industry and academic circles have directed their attentions towards Optical Character Recognition. Over the last few years, the number of academic laboratories and companies involved in research on Character Recognition has increased dramatically. This research aims at summarizing the research so far done in the field of OCR. It provides an overview of different aspects of OCR and discusses corresponding proposals aimed at resolving issues of OCR.

A Study of Optical Character Patterns identified by the different OCR Algorithms

Optical Character Recognition (OCR) is a technology that provides a full alphanumeric recognition of printed or handwritten characters. Optical Character Recognition is one of the most interesting and challenging research areas in the field of Image processing. Image Acquisition, Pre-processing, Segmentation, Feature Extraction and Classification are stages of OCR. In this paper, how character patterns are identified in the classification stage by different algorithms is presented. Template Matching Algorithm, statistical Algorithm, Structural Algorithm, Neural Network Algorithm and Support Vector Machine Algorithm are presented in this paper.

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.

Optical Character Recognition Techniques A Survey

This paper presents a literature review on English OCR techniques. English OCR system is compulsory to convert numerous published books of English into editable computer text files. Latest research in this area has been able to grown some new methodologies to overcome the complexity of English writing style. Still these algorithms have not been tested for complete characters of English Alphabet. Hence, a system is required which can handle all classes of English text and identify characters among these classes.

OPTICAL CHARACTER RECOGNITION TECHNIQUE ALGORITHMS

In this paper, we present a new neural network (NN) based method for optical character recognition (OCR) as well as handwritten character recognition (HCR). Experimental results show that our proposed method achieves increased accuracy in optical character recognition as well as handwritten character recognition. We present through an overview of existing handwritten character recognition techniques. All the algorithms describes more or less on their own. Handwritten character recognition is a very popular and computationally expensive task; we describe advanced approaches for handwritten character recognition. In the present work, we would like to compare the most important once out of the variety of advanced existing techniques, and we will systematize the techniques by their characteristic considerations. It leads to the behaviour of the algorithms reaches to the expected similarities.