OCR Optical Character Recognition

Optical Character Recognition Systems

Abstract Optical character recognition (OCR) is process of classification of optical patterns contained in a digital image. The character recognition is achieved through segmentation, feature extraction and classification. This chapter presents the basic ideas of OCR needed for a better understanding of the book. The chapter starts with a brief background and history of OCR systems. Then the di...

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 longt...

OCR for printed Kannada text to Machine editable format using Database approach

This paper describes an Optical Character Recognition (OCR) system for printed text documents in Kannada, a South Indian language. The proposed OCR system for the recognition of printed Kannada text, which can handle all types of Kannada characters. The system first extracts image of Kannada scripts, then from the image to line segmentation then segments the words into sub-character level piece...

Number Plate Recognition Using Ocr Technique

Automatic Number Plate Recognition (ANPR) is a special form of Optical Character Recognition (OCR). ANPR is an image processing technology which identifies the vehicle from its number plate automatically by digital pictures. In this paper we have presented an algorithm for vehicle number identification based on Optical Character Recognition (OCR). OCR is used to recognize an optically processed...

Arabic Optical Character Recognition (OCR) Evaluation in Order to Develop a Post-OCR Module

Cryptogram Decoding for Optical Character Recognition

Optical character recognition (OCR) systems for machine-printed documents typically require large numbers of font styles and character models to work well. When given a document printed in an unseen font, the performance of those systems degrade even in the absence of noise. In this paper, we perform OCR in an unsupervised fashion without using any character models by using a cryptogram decodin...