The recognition of cursive script is regarded as a subtle task in optical character recognition due to its varied representation. Every cursive script has different nature and associated challenges. As Urdu is one of cursive language that is derived from Arabic script, that’s why it nearly shares the same challenges and difficulties even more harder. We can categorized Urdu and Arabic language ...

An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described in the paper. A new method, called, diagonal based feature extraction is introduced for extracting the features of the handwritten alphabets. Fifty data sets, each containing 26 alphabets written by various people, are used for training the neural network and 570 different...

This paper presents a method of recognition of isolated offline handwritten Devanagari numerals using wavelets and neural network classifier. This method of optical character recognition takes the handwritten numeral image as input. After pre-processing, it is subjected to single level wavelet decomposition using Daubechies-4 wavelet filter. This wavelet decomposition allows viewing the input n...

For many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. However, an issue that has rarely been studied is the speed of these methods. Considering the computer hardware limitations, it is necessary for these methods to run in high speed. One of the methods to increase the processing speed is to use the computer pa...

<p>Automated reading of handwritten Kannada documents is highly challenging due to the presence vowels, consonants and its modifiers. The variable nature handwriting styles aggravates complexity machine based vowels consonants. In this paper, our investigation inclined towards design a deep convolution network with capsule routing layers efficiently recognize characters. Capsule architect...

Optical character recognition (OCR) is very popular research field since 1950’s. A great work has been done for various scripts particularly in case of English. But in case of Indian scripts the research is limited. This paper presents an overview of the various O.C.R. systems for gurmukhi which are developed for handwritten isolated gurmukhi text. In case of printed gurmukhi text a lot of rese...

Handwriting recognition is one of the most challenging tasks and exciting areas of research in computer vision. Numerous document recognition methods have been proposed in various languages and character set such as Arabic, India, Korean, Japanese, Chinese and so on. This paper presents the recent result of the research work of Myanmar handwriting text recognition and translation. Each segmente...

This paper discusses online handwriting recognition of Japanese characters, a mixture of ideographic characters (Kanji) of Chinese origin, and the phonetic characters made from them. Most Kanji character patterns are composed of multiple subpatterns, called radicals, which are shared among many (sometimes hundreds of) Kanji character patterns. This is common in Oriental languages of Chinese ori...

Handwritten character recognition has been studied a lot in the past and involves various problems due to many reasons. In this paper, novel method of Handwritten Marathi Barakhadi Character Recognition with Shape and Texture features has been proposed. The Shape features and Texture feature are more unique, so a novel technique based on combination of these is derived and proposed here. For ex...

Handwritten character recognition plays an important role in the modern world. It can solve more complex problems and makes human’s job easier. The present paper portrays a novel approach in recognizing handwritten devanagari character through feed forward back propagation neural network. All the experiments are conducted by using the Artificial Neural Network tool of Matlab.