The accuracy of Optical Character Recognition (OCR) is crucial to the success of subsequent applications used in text analyzing pipeline. Recent models of OCR post-processing significantly improve the quality of OCR-generated text, but are still prone to suggest correction candidates from limited observations while insufficiently accounting for the characteristics of OCR errors. In this paper, ...

The OCR-algorithm (optical character recognition) described in this paper is a module in the assistive device SubPal, which should be able to read subtitles from television and camera aloud. The SubPal system is described in detail in (Nielsen & Bothe, 2007). By sampling the television signal (PAL) a binary image is created. This binary image is analysed using the OCR-algorithm for generating t...

This paper gives an overview on the development process and ongoing research of the optical character recognition (OCR) systems for Telugu Text. The aim of this paper is to provide a starting point for the researchers entering into this field. In this paper, we present the introduction, characteristics of the Telugu language, developmental process of the OCR systems of Telugu language, research...

Slant Correction is an important component of an Optical Character Recognition (OCR) system. The stronger the slant correction algorithm, the better the OCR system’s performance. In this work, a non-uniform slant estimation algorithm is presented. The algorithm uses the generalized projections of the word image. The algorithm is simple and robust. To evaluate the efficacy of the algorithm, imag...

This article discusses two major initiatives tasked with developing tools to improve optical character recognition (OCR) or the mechanical keying of texts that are digitally available only as page images. The two initiatives are the IMProving ACcess to Text Project in Europe and the Early Modern OCR Project in the USA. Because of dealing with a multilayered problem like OCR technologies and hav...

In this paper, we present an approach to construct an optical character recognition (OCR) system for recognizing rotated printed Chinese characters. Our system includes preprocessing, feature extraction, candidates selection, and target character recognition. The proposed system has a three-stage structure designed mainly to reduce the time complexity in the recognition process. Our goal is to ...

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial...

Optical music recognition (OMR) enables librarians to digitise early music sources on a large scale. The cost of expert human labour to correct automatic recognition errors dominates the cost of such projects. To reduce the number of recognition errors in the OMR process, we present an innovative approach to adapt the system dynamically, taking advantage of the human editing work that is part o...

The character recognition is the major important part in the area of document analysis. Character Recognition could be evaluated on printed text and handwritten text. Printed texture could be from a good quality image. In this research work, we implemented in the OCR approach to improve the recognition of character with Classification approach. We work on filtration techniques to improve the pi...

Optical Character Recognition (OCR) systems for Arabic rely on information contained in the scanned images to recognize sequences of characters and on language models to emphasize fluency. In this paper we incorporate linguistically and semantically motivated features to an existing OCR system. To do so we follow an n-best list reranking approach that exploits recent advances in learning to ran...