Abstract Migrating large amount of texts and images from the traditional print to digital format involves many issues and challenges despite the technology we have. One major issue is that many languages have different scripts and unique nature and the international protocols fail to comply with the uniqueness of languages. Myanmar is one such special language which has an exclusive script system. We in this paper, propose a method for converting Myanmar print text and images to machine readable formats. In this multi stage method, first task is the correction of noise variants using a unique segmentation way followed by a few more stages. We have deployed the SVM classifier for understanding and reading the character image. Our experimental results show promising outcome. Read More Read Less

Abstract End users resort to varied ways of text searching in text; however most of them rely on key word approach and hence in the Information Retrieval research, it is often provided priority. Data is being stored in relational databases where keyword based search has difficulties. Thus there is a need to introduce a keyword searching compatibility in relational database search. We in this paper introduce the way of indexing the records, followed by key word matching and finally the distilling result key words. Our system is found to score than the existing systems in the retrieval efficiency in the experimentation. Read More Read Less