In this paper, we propose a novel scheme for recognition of handwritten numerals for a regional language Odia of the Indian continent. Additional attempts have also been made to implement this scheme for recognition of handwritten numerals of two other languages namely, Bangla and English. Thus, the proposed scheme has been generalised to three different languages. Three variants of time series...

This paper proposes a model-based structural matching method for handwritten Chinese character recognition (HCCR). This method is able to obtain reliable stroke correspondence and enable structural interpretation. In the model base, the reference character of each category is described in an attributed relational graph (ARG). The input character is described with feature points and line segment...

This paper presents writer-independent offline handwritten character recognition for Ethiopic script. The recognition is based on the characteristics of primitive strokes that make up characters. The spatial relationships of primitives whose combinations form complex structures of Ethiopic characters are used as a basis for recognition. Although this approach efficiently recognizes properly wri...

Researchers have thus far focused on the recognition of alpha and numeric characters in isolation as well as in context. In this paper we introduce a new genre of problems where the input pattern is taken to be a pair of characters. This adds to the complexity of the classi"cation task. The 10 class digit recognition problem is now transformed into a 100 class problem where the classes are M00,...

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...

Leipzig University’s (LU) Alexander von Humboldt Chair for Digital Humanities—has achieved Optical Character Recognition (OCR) accuracy rates for classical Arabic-script texts in the high nineties. These numbers are based on our tests of seven different Arabic-script texts of varying quality and typefaces, totaling over 7,000 lines (~400 pages, 87,000 words; see ​Table 1​ for full details). The...

In a multilingual country like India, a document may contain text words in more than one language. For a multilingual environment, multi lingual Optical Character Recognition (OCR) system is needed to read the multilingual documents. So, it is necessary to identify different language regions of the document before feeding the document to the OCRs of individual language. The objective of this pa...

Different character recognition problems have their own specific characteristics. The state-of-art OCR technologies take different recognition approaches, which are most effective, to recognize different types of characters. How to identify character type automatically, then use specific recognition engines, has not brought enough attention among researchers. Most of the limited researches are ...