In this paper, a new proposed system for Persian printed numeral characters recognition with emphasis on representation and recognition stages is introduced. For the first time, in Persian optical character recognition, geometrical central moments as character image descriptor and fuzzy min-max neural network for Persian numeral character recognition has been used. Set of different experiments ...

This paper presents a model and its effect for on-line handwritten Japanese text recognition free from line-direction constraint and writing format constraint such as character writing boxes or ruled lines. The model evaluates the likelihood composed of character segmentation, character recognition, character pattern structure and context. The likelihood of character pattern structure considers...

Real-time character recognition in video frames has been attracting great attention from developers since scene text recognition was recognized as a new field of Optical Character Recognition (OCR) applications. There are thousands of characters in some oriental languages such as Japanese and Chinese, and the character recognition takes much longer time in general compared with European languag...

Character recognition techniques associate a symbolic identity with the image of character. Character recognition software recognizes text characters in electronic files, usually scanned documents that are saved as images and are not immediately text-searchable. Character recognition software is also known as optical character recognition or OCR, because it uses to optical properties of text to...

Grayscale feature is very effective for degraded character recognition. While many papers focus on different feature extraction algorithms on single character recognition, few deals with the impact of the selected feature on segmentation. For recognition-based segmentation, a good recognition performance on single character may not always have good performance on segmentation. In this paper, tw...

To utilize a character information in scene images, character recognition and segmentation are required. Character segmentation is essential preliminary of character recognition. However, most character segmentation methods cannot extract isolated characters which do not constitute a character string, characters in a complex equation, touching characters where two characters are connected and s...

Arabic script character recognition is challenging task due to complexity of the script and huge number of ligatures. We present a method for the development of multilingual Arabic script OCR (Optical Character Recognition) and lexicon reduction for Arabic Script and its derivative languages. The objective of the proposed method is to overcome the large dataset Urdu and similar scripts by using...

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...