The development of a Character recognition system for Devnagri is difficult because (i) there are about 350 basic, modified (“matra”) and compound character shapes in the script and (ii) the characters in a words are topologically connected. Here focus is on the recognition of offline handwritten Hindi characters that can be used in common applications like bank cheques, commercial forms, gover...

The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode) [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for...

Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the pres...

In this paper, a zone based symmetric density feature is proposed to recognize Handwritten Marathi Vowels. Recognition of handwritten Marathi vowels is a challenging task due to their interclass structural similarities. This paper describes a method for recognition of handwritten Marathi vowels. Since a standard database does not exist for handwritten Marathi vowels, as a part of this work data...

Persian is a challenging language in the field of NLP. Rightto-left orthography, complex morphology, complicated grammatical rules, and different forms of letters make it an interesting language for NLP research. In this paper we measure the effectiveness of a simple and efficient stemming algorithm, Perstem, on Persian information retrieval. Our experiments on the Hamshahri corpus at CLEF2009 ...

This paper introduces a novel design for handwritten letter recognition by employing a hybrid back-propagation neural network with an enhanced evolutionary algorithm. Feeding the neural network consists of a new approach which is invariant to translation, rotation, and scaling of input letters. Evolutionary algorithm is used for the global search of the search space and the back-propagation alg...

This paper explores the existing ring based [2], the new sector based and the combination of these, termed as Fusion method for the recognition of handwritten English capital letters. The variability associated with the characters is accounted for by way of considering a fixed number of concentric rings in the case of ring based approach and a fixed number of sectors in the case of sector appro...

In this paper, we present a new neural network (NN) based method for optical character recognition (OCR) as well as handwritten character recognition (HCR). Experimental results show that our proposed method achieves increased accuracy in optical character recognition as well as handwritten character recognition. We present through an overview of existing handwritten character recognition techn...