The Optical Character Recognition is the electronic conversion of image of typewritten or printed text into machine-encoded text. It is common method of digitizing printed texts. Advantages being easy storage, edit ability, searching, etc. OCR is a field of research in pattern recognition, artificial intelligence and computer vision. In previous decades it has gain more importance due to feasib...

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 techn...

A public domain document processing system has been developed by the National Institute of Standards and Technology (NIST). The system is a standard reference form-based handprint recognition system for evaluating optical character recognition (OCR), and it is intended to provide a baseline of performance on an open application. The system’s source code, training data, performance assessment to...

into the present pdf format file from an original copy of the published article. To reduce the size of the file, the scanned images were converted to text using OCR software, prior to converting to the final pdf file that you are now reading. Please note that occasionally this process introduces errors that were not in the original. We have attempted to correct such errors, but acknowledge that...

Crowdsourcing approaches for post-correction of OCR output (Optical Character Recognition) have been successfully applied to several historic text collections. We report on our crowd-correction platform Kokos, which we built to improve the OCR quality of the digitized yearbooks of the Swiss Alpine Club (SAC) from the 19th century. This multilingual heritage corpus consists of Alpine texts mainl...