Abstract Optical Character Recognition (OCR) has become one of the most important techniques in computer vision, given that it can easily obtain information from various images. However, existing OCR cannot recognition Telugu literature characters (Handwritten Golusu Kattu writing) due to a lack datasets and trained deep Convolutional Neural Networks (CNN). Since Kakatiya Empire (12 th 14 centu...

K E Y W O R D S online handwritten Tibetan character recognition, de-noising, pre-processing, three-stage classification This is a contribution from Himalayan Linguistics, Vol. 15(1): 31–40. ISSN 1544-7502 © 2016. All rights reserved. This Portable Document Format (PDF) file may not be altered in any way. Tables of contents, abstracts, and submission guidelines are available at escholarship.org...

A new feature extraction approach based on elastic meshing and directional decomposition techniques for handwritten Chinese character recognition (HCCR) is proposed in this letter. It is found that to decompose a Chinese character into horizontal, vertical stroke, left slant and right slant directional sub-pattenrs is very helpful for feature extraction and recognition. Three kinds of decomposi...

Optical character recognition (OCR) is used to digitize texts in printed documents and camera images. The most basic step the OCR process recognition. Arabic language more complex than other alphabets, as cursive written characters have different spellings. Our research has improved a model for with 28 characters. Character was performed using Convolutional Neural Network models, which are acce...

Artificial Neural Network (ANN) s has widely been used for recognition of optically scanned character, which partially emulates human thinking in the domain of the Artificial Intelligence. But prior to recognition, it is necessary to segment the character from the text to sentences, words etc. Segmentation of words into individual letters has been one of the major problems in handwriting recogn...