Book digitizing is an important work in preserving ancient heritages. However, digitizing books contains a series of labor-intensive works, and one of them is to verify optical character recognition (OCR) outcomes. In this paper, we propose a crowdsourceable OCR verification method. Using our method, content holders are able to leverage the power of crowds to complete verification tasks and avo...

Depending on the quality of the original document, Optical Character Recognition (OCR) can produce a range of errors – from erroneous letters to additional and spurious blank spaces. We applied a sequence-to-sequence machine translation system to correct word-segmentation OCR errors in scientific texts from the ACL collection with an estimated precision and recall above 0.95 on test data. We pr...

Rigorous research has been done on optical character recognition (OCR) and a large number of articles have been published on this topic during the last few decades. OCR plays a vital role in Digital Image Processing and Pattern Recognition. Numerous work has stated for Roman, Chinese, Japanese and Arabic scripts. There is no convenient work done on Indian script recognition. In India, more than...

Techniques which may reduce the false alarm rate of sliding networks employed in ASR (automatic speech recognition) and OCR (optical character recognition) problems are reviewed. Such techniques include the use of hypersphere classifiers, training out of negatives, addition of garbage units, and exploitation of multiple networks. The combination of several techniques may reduce the false alarm ...

In this study, we propose an optical character recognition technique using Intro Sort. Main feature of this proposed technique is that we segment images using intro sort. It reduces the comparison time for matching the pixels of an image. It reflects reduction in OCR time. Intro sort algorithm begins with quick sort and when recursion depth exceeds a level it switches to heap sort, based on the...

Optical Character Recognition (OCR) using Android has been received a great attention. In all these efforts a flat document is selected for OCRing and non-flat documents are ignored. Labels mounted on cylindrical surfaces such as wine bottle, pill box, cans, etc, are examples of non-flat documents. The goal of this research effort is to perform optical character recognition on a non-flat docume...

Recognition of Indian languages is a challenging problem. In Optical Character Recognition (OCR), acharacter or symbol to be recognized can be machine printed or handwritten characters/numerals. Several approaches in the past have been proposed that deal with problem of recognition of numerals/character depending on the type of feature extracted and way of extracting them. In this paper also a ...

of the Dissertation Geometric Methods for Optical Character Recognition by George N. Sazaklis Doctor of Philosophy in Computer Science State University of New York at Stony Brook Advisor: Joseph S. B. Mitchell 1997 Abstract Optical Character Recognition (OCR) is an important problem having both theoretical and practical interest. In this dissertation, we present solutions to three problems with...

Optical character recognition (OCR) computer systems are widely used for of car license plates, enabling visually impaired people to work with written information, etc. One the current areas OCR problems is handwritten characters. This study proposes approaches construction combined models using simple and ensemble learning letters Azerbaijani language. The built proposed utilized several class...

In many documents machine printed& handwritten texts are intermixed .Optical Character Recognition (OCR) techniques are different for machine printed and handwritten text, so it is necessary to separate these text before giving input to the OCR. In this paper we are proposing methodology for Hindi language. This methodology is based on structural features of text. Experimental results on a data...