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.

Guide to OCR for Indic Scripts: Document Recognition and Retrieval

Abstract: This unique guide/reference is the very first comprehensive book on the subject of OCR (Optical Character Recognition) for Indic scripts. Features: contains contributions from the leading researchers in the field; discusses data set creation for OCR development; describes OCR systems that cover 8 different scripts Bangla, Devanagari, Gurmukhi, Gujarati, Kannada, Malayalam, Tamil, and Urdu (Perso-Arabic); explores the challenges of Indic script handwriting recognition in the online domain; examines the development of handwriting-based text input systems; describes ongoing work to increase access to Indian cultural heritage materials; provides a section on the enhancement of text and images obtained from historical Indic palm leaf manuscripts; investigates different techniques for word spotting in Indic scripts; reviews mono-lingual and cross-lingual information retrieval in Indic languages. This is an excellent reference for researchers and graduate students studying OCR technology and methodologies.

Offline Handwritten Devanagari Script Recognition

Abstract: Handwritten Devanagari script recognition system using neural network is presented in this paper. Diagonal based feature extraction is used for extracting features of the handwritten Devanagari script. After that these feature of each character image is converted into chromosome bit string of length 378. More than 1000 sample is used for training and testing purpose in this proposed work. It is attempted to use the power of genetic algorithm to recognize the character. In step-I preprocessing on the character image, then image suitable for feature extraction as here is used. Diagonal based feature extraction method to extract 54 features to each character. In the next step character recognize image in which extracted feature in converted into Chromosome bit string of size 378. In recognition step using fitness function in which find the Chromosome difference between unknown character and Chromosome which are store in data base.

A Journey from Indian Scripts Processing to Indian Language Processing

Abstract: This overview examines the historical development of mechanizing Indian scripts and the computer processing of Indian languages. While examining possible solutions, the author describes the challenges involved in their design and in exploiting their structural similarity that lead to a unified solution. The focus is on the Devanagari script and Hindi language, and on the technological solutions for processing them.

Performance Comparison of Features on Devanagari Hand-printed Dataset

Abstract: Devanagari script is being used in various languages, in south Asian subcontinent, such as Sanskrit, Rajasthani, Marathi and Nepali and it is also the script of Hindi, the mother tongue of majority of Indians. Recognition of handwritten characters of Devanagari alphabet set is an important area of research. The work done for the recognition of Devanagari handwritten script is negligible in literature despite it is being used by millions people in India and abroad and it has numerous applications. The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. There are many feature extraction methods available in literature. We have tested the recognition performance of about 5 feature extraction methods available in literature on Devanagari handwritten characters. A database of more than 25000 handwritten Devanagari characters is developed by collecting the samples from hundreds writers belonging to 43 Devanagari alphabets. The performance comparisons have been made using two classifiers MLP and SVM.