Title: Improving Text Translation from Images with MSER Algorithm

Year of Publication: Sep - 2015
Page Numbers: 82-89
Authors: Sruthi N , Kamal Bijlani
Conference Name: The Fourth International Conference on E-Learning and E-Technologies in Education (ICEEE2015)
- Indonesia

Abstract:


Translators play an important role in conveying ideas and thoughts from one language to another. A contextual based approach to translation of English words from images to the equivalent Hindi words is described in this paper. Text segmentation is an integral and critical process in text extraction which have the major control over the accuracy of any translator. The paper describes a study on text segmentation algorithm with Maximally Stable Extremal Regions (MSER) which is implemented as a preprocessing module of the translation system. Initially the system learns through user disambiguation of appropriate words in the sentence. However, once the system has learned enough contextual information, it performs the automatic translation. The experimental results of segmentation are compared and analyzed. Such a system has a number of uses, including e-learning of the English language as well as for Indian tourists from overseas countries. It can be applied for learning any courses. The system can also be extended to include other Indian languages.