Transliteration of Indian Ancient Script to Braille Script using Pattern Recognition Technique: A Review
Kirti  Mahajan bharatividyapeeth.academia.edu
Transliteration of Indian Ancient Script to Braille Script using Pattern Recognition Technique: A Review
After the printed character recognition handwritten character recognition is always a leading area of research in the field of pattern recognition. Even though, sufficient studies have performed in foreign scripts like Arabic, Chinese and Japanese, only a very few work can be traced for handwritten character recognition mainly for the south Indian, Devanagari scripts. OCR system development for Indian script has many application areas like banking, libraries, preserving manuscripts and ancient literatures written in different Indian scripts and making digital libraries for the documents. Feature extraction and classification are the two essential steps of character recognition process affecting the overall accuracy of the recognition system. This survey represents a history of character recognition with digital image processing techniques such as Feature Extraction, classification, Image Restoration and Image Enhancement.

English, Tamil, Kannada Ancient scripts are widely studied in the last few years in India. In India, Several peoples are using Devanagari script for Documentation. Marathi is one of the popular languages which uses this script. To study Indian history, the inscriptions are playing a vital role as a resource. Marathi Scripts are handy Ancient words in India. Ancient Marathi Scripts are made up of Devanagari Characters. In this research paper study Ancient Marathi Scripts based on Ancient Indian documents written on the stone using modern digital image processing techniques is reviewed. In Ancient Marathi Script, the classification of Marathi manuscripts was carried out by using the style of handwriting. Preserving old archive readable and editable structure helps gain additional information about Ancient Marathi Scripts. Ancient Marathi Script Recognition is used as an information extraction method for the modern dictionary. Mostly Ancient Scripts Recognition is a useful source for researcher who work in the area of Archaeology and Social Science field people.

This paper describes the classification of a subset of printed or digitized Gujarati characters. Gujarati belongs to the genre of Devanagari scripts from the Indian subcontinent. Very little work is found in the literature for recognition of Indian language scripts. For this paper a subset of similar appearing Gujarati characters was chosen and subjected to classification by different classifiers. The sample and test images for the characters were obtained from digital images available on the Internet and from scanned images of printed Gujarati text. For their classification, the Euclidean Minimum Distance and the k–Nearest Neighbor classifiers were used with regular and invariant moments. The characters were also classified in the binary feature space using Hamming Distance classifier. The paper presents the recognition rates for these classifiers. A recognition rate is achieved. The work described in this paper is preliminary; however, since ICDAR’99 is being held in India, we hop...

Rigorous Research has been done on ancient Indian script character recognition. Many research articles are published in last few decades. Number of OCR techniques is available in market, but OCR techniques are not useful for ancient script recognition. But more research work is required to recognize ancient Marathi scripts. This paper presents different techniques which are published by different researchers to recognize ancient scripts. Also challenges in recognition of ancient Marathi scripts are discussed in this paper.

In this paper, we describe the different techniques of character recognition for Gujarati and Devanagari script. Character recognition is usually referred to as OCR. Review of this paper will provide a way for researcher to develop a tool for Gujarati and Devanagari script recognition. This paper describes basics of character recognition, its type, challenges associated with it and the special properties of Gujarati and Devanagari script.

Braille is a language of utmost importance for the upliftment of blind people. One of the problem with education of blind people is the unavailability of resources such as books etc. which are mostly in local languages being used by general people. Recently there have been lots of works done to automate the process of translating books in English, Arabic etc. into Braille as typing the whole book is very cumbersome. This paper is proposing an algorithm to convert any scanned handwritten document in Hındi to corresponding Braille. It uses Histogram of oriented gradients features of Hindi characters for matching in an SVM classifier. The scanned documents are first converted into a printable form and then transliterated to Braille using UTF-8 codes.

India is a multilingual country. A significantly large number of scripts are used to represent these languages. A desire of vision researchers is to develop an integrated optical character recognition (OCR) system, which will be able to process all such scripts. Such a development, if objectified, will not only enable faster flow of information across the country, but also have a profound effect on its scientific and economical development. Courageous endeavours have been successfully made towards the development of systems capable of recognizing machine-printed or handwritten characters and/or numerals. However, most Indian scripts do not have an integrated OCR system. Further, the development of a unified system, which is capable of processing all Indian scripts is still a dream. This article presents a survey of the current literature on the development of OCR's in Indian scripts. Reviewing the basis of and the motivation towards the development of OCR system, the article analyzes the various methodologies employed in general purpose pattern recognition systems. A critical analysis of the work towards OCR systems in Indian languages, with pointers towards possible future work, is also presented.