Abstract
Recognition of handwritten numerals has been one of the most challenging topics in image processing. This is due to its contributions in the automation process in several applications. The aim of this study was to build a classifier that can easily recognize offline handwritten Arabic numerals to support those applications that are deal with Hindi (Arabic) numerals. A new algorithm for Hindi (Arabic) Numeral Recognition is proposed. The proposed algorithm was developed using MATLAB and tested with a large sample of handwritten numeral datasets for different writers in different ages. Pattern recognition techniques are used to identify Hindi (Arabic) handwritten numerals. After testing, high recognition rates were achieved, their ranges from 95% for some numerals and up to 99% for others. The proposed algorithm used a powerful set of features which proved to be effective in the recognition of Hindi (Arabic) numerals.
Highlights
The development of Optical Character Recognition system OCR is considered one of the most important fields of research areas in pattern recognition
The aim of this study was to build a classifier that can recognize offline handwritten Arabic numerals to support those applications that are deal with Hindi (Arabic) numerals
The recognition of handwritten numerals becomes an intensive area of research; in order to increase the functionality of OCR system
Summary
The development of Optical Character Recognition system OCR is considered one of the most important fields of research areas in pattern recognition. OCR allows a machine to automatically recognize characters through an optical mechanism. In other words, it is electronic translation for the images of handwritten numerals into computer textual format. The recognition of handwritten numerals becomes an intensive area of research; in order to increase the functionality of OCR system. Numeral recognition systems can be utilized in several applications such as: check verification in banks, office automation, postal address reading and communication technology. There are several approaches that deal with numerals/characters recognition problem, each approach depends on a set of features to be extracted and the ways of extracting them
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