Recognition of handwritten Arabic text awaits accurate recognition solutions. There are many difficulties facing a good handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, and their position in the word. The typical Optical Character Recognition (OCR) systems are based mainly on three stages, preprocessing, features ...

This paper deals with accuracy improvement of handwritten character recognition by the GLVQ (generalized learning vector quantization). In literature , the way of combining the FDA (Fisher discriminant analysis) and the GLVQ was investigated and evaluated to be effective for handwritten Chinese character recognition employing the minimum Euclidian distance classifier. In this paper, the project...

This paper presents an approach to recognize off-line Bangla numeral. Today there are many OCR used to recognize Bangla numeral. The recognition of handwritten character is still a challenging work in the field of pattern recognition. Numeral recognition in pattern recognition is the process to identify the given character according to the predefined character set. The difficulties of recogniti...

Traditional approaches for handwritten Chinese character recognition suffer in classifying similar characters. In this paper, we propose to discriminate similar handwritten Chinese characters by using weakly supervised learning. Our approach learns a discriminative SVM for each similar pair which simultaneously localizes the discriminative region of similar character and makes the classificatio...

In this paper, work has been performed to recognize Handwritten English Character using a multilayer perceptron with one hidden layer. The feature extracted from the handwritten character is Boundary tracing along with Fourier Descriptor. Character is identified by analyzing its shape and comparing its features that distinguishes each character. Also an analysis was carried out to determine the...

Highly accurate optical character recognition (OCR) of handwritten characters is still a challenging task, especially for languages like Chinese and Japanese. To improve the accuracy, we developed four techniques for enhanced recognition: character recognition based on modified linear discriminant analysis (MLDA), subspace-based similar-character discrimination, multi-classifier combination, an...

The Character Recognition of both typed as well as handwritten characters is still an open area of research. Although significant success has been achieved in type written characters but in handwritten it is still to touch an appreciable level. This research proposes an approach of character recognition which besides producing better results of recognition is extremely less complicated as compa...