Devanagari

About: Devanagari is a research topic. Over the lifetime, 655 publications have been published within this topic receiving 7428 citations. The topic is also known as: Deva nagari & Hindi Script.

OCR For Handwritten Marathi Script

Abstract: Optical Character Recognition which is the original method of character recognition many times gives poor recognition rate due to error in character segmentation. Segmentation is an important task of any OCR system. It separates the image text documents into lines, words and characters. The accuracy of OCR system mainly depends on the segmentation algorithm being used. Segmentation of Handwritten Devanagari text is difficult when compared with Printed Devanagari or Printed English or any other Printed document its structural complexity and increased character set. It contains vowels, consonants. Some of the characters may overlap together. The profile based methods can only segment non-overlapping lines and characters. This paper addresses the segmentation of Handwritten Devanagari text document, the most popular script of Indian sub-continent into lines, words and characters. The proposed algorithm is based on projection profiles. Experimental results it is observed that 100% line segmentation and about 98% character segmentation accuracy can be achieved with overlapping lines, words and characters.

Testing the efficacy of an Indic script virtual keyboard: Swarachakra

Abstract: Indian text input is an area which is now being studied by not only language experts but designers and developers. Since a decade there is work in progress for designs that are intended to develop easy and efficient keyboard for different Indian Languages scripts. Swarachakra (for android) is one novel attempt to resolve this problem. In our studies we found that alphabetical keyboard layout performed better than the Inscript layout for Devanagari Script.This case study discusses the evaluation and evolution of Swarachakra as virtual keyboard. It talks about the various degrees of usability testing which has been done to check its efficacy. User group included were students, adults and elder people with literacy level varying from graduate to low literate. The results of the study shows that with minimal training, a user is able to achieve acceptable comfort and speed with the logical design based keyboard.

A Survey on Offline Recognition of Handwritten Devanagari Script

Abstract: Devanagari Script is mostly useful in India for writing number of official forms and documents, especially in the banking applications for writing amount in words on the cheque. The Offline recognition of handwritten Devanagari script has great application in automatic processing of handwritten bank cheques images, documentation of various official documents as well as digitization of government and non government documents. In this paper it has been tried to achieve automatic recognition of handwritten Devanagari Script by using various algorithms.

Script Reform in Modern India, Pakistan, and Ceylon

Abstract: IN INDS:A, Pakistan and Ceylon today it is possible to see script reform in progress. We can identify forces leading toward change and factors that retard or shape it. Though the principal scripts of those countries have in the past usually been successful means of writing the languages that use them, they now need to be adapted to new cond.itions. All the scripts of the area used in priilting are so affected, but the pressure is greatest upon those used where modernization of the national life is proceeding most rapidly. The scripts involved belong to two dif3Serent families. One is the Indic script family, the modern members of which are all descended from the Brahml script known first in inscriptions of the 3rd century B. C.1 They employ certain eommon principles, though in their more than two millennia of development the separate scripts have often acquired widely diSering shapes of corresponding characters. Prominent contemporary members of this family now subject to reform are Devanagari or Nagari (used for ELindi, Marathi, Bihari, Rajasthani, and more frequently than any other script for Sanskrit), Bengali (also used for Assamese), Gujarati, Tamil, Telugu, Kanara, Malayalam, Sinhalese. Other members of the family likely at any time to become subject to reform are Oriya and Gurmukhi (used by Sikhs for Punjabi). These all read from left to right. Features which suggest a need for reform are the following. First, these scripts consider that the basic form of each consonant has the vowel short a as an inherent element which does not need to be otherwise indicated when it occurs after the consonant in pronunciation. All other vowels have

Handwriting Recognition Using Active Contour

Abstract: Handwriting recognition is the process of recognizing handwritten or printed alphabets in various documents and even old manuscript. This method also helps in preserving the texts and writings of ancient times. This paper aims to represent the work related to recognition of cursive handwriting of different languages. Cursive handwritings are connected to each other, hence segmentation is required. Segmentation is used for extraction: line segmentation to extract sentence, word segmentation to extract words and character segmentation to extract individual letters. The segmentation involves dividing based on contours by setting different kernel size. For classification, we have used classifiers—convolution neural networks. We carried our experiment using datasets collected from E-MNIST, UCI. The experimental accuracy for the E-MNIST dataset is 79.3% and for UCI Devanagari dataset is 93%.