Energy Efficient Business Card Recognition and Translation Over Cloud Computing using Google Vision

Developments in cloud computing and smart phone technology have opened the door for many unique applications to be created. In a world that is interminable becoming more globalize, there are more interactions between different languages. One of such applications is the ability to allow users to use computer vision with a camera on their phone to translate foreign language into their native language. However, early adopters of this. Technologies are far from optimal when it comes to features and robustness of their apps. Exploring options for optimizing allocation of resources and maximizing features of these apps can greatly improve the technology for users and distributors alike. In this project we introduce a scalable and energy efficient computer vision protocol for the text translation using Google Vision and reduce power consumption by uploading the translation computation on server, improving the data usage, and accuracy of translation. Our proposed idea is based on a camera driven process algorithm and an energy-efficient model to improve energy efficiency and provide the scalability support for foreign language translation. To validate the proposed idea, a Java based platform is developed. Our results demonstrate that compared the existing application with our application energy efficient and scalable application showed much better performance than existing applications including Google App. Citation: Ashwini A. Shinde, LoGMIEER, Nashik; Malini D. Tungar ,LoGMIEER, Nashik; Pooja S. Khairnar ,LoGMIEER, Nashik; Jyoti S. Gunjkar ,LoGMIEER, Nashik. "Energy Efficient Business Card Recognition and Translation Over Cloud Computing using Google Vision." Global Research and Development Journal For Engineering 24 2017: 80 - 84.