The Indian subcontinent houses 1,652 different languages. Communication between the central and state government occurs through the exchange of documents in English or Hindi. Kannada is the official language of Karnataka, a southern Indian state. State officials are often well versed in Kannada and prefer it over other languages. The motivation for this capstone project was to aid government offices by providing a medium for translating documents written in English to Kannada in a cost-effective way. Moreover, existing techniques are constrained by the orientation of input images, requiring users to capture input images at specific angles. This paper proposes a novel, semi-automated methodology that facilitates precise text extraction from document images captured via mobile phone and supports English to Kannada translation. The proposed system was evaluated on a database of document images and achieved precision of 0.9, recall of 0.92, F measure of 0.91 which is comparable to state-of-art techniques.
Published In:IJCSN Journal Volume 9, Issue 2
Date of Publication : April 2020
Pages : 79-92
Tables : 02
Chirag Kamath :
is pursuing his Bachelor of Engineering degree and is a final year student at BMSCE, Department of Information Science and Engineering. He is currently an Associate Software Engineering Intern at Sabre Corp and has previous industry experience as a summer intern at IBM. His research interests include AI & image processing.
Neha Prakash :
is currently pursuing her Bachelor of Engineering degree at BMSCE, Department of Information Science and Engineering. She is currently working at Clumio Inc as a Software Engineering Intern. She has previously interned at American Express.
Dr Radhika K R :
is a professor at B.M.S College of Engineering. She has an experience of 23 years in teaching a wide area of subjects in Information Science Department at BMSCE. She received her Phd in 2010 and Mtech in 2000 from Vishesvaraya and Bangalore University respectively. She has 40+ publications in various reputed journal. She is a senior member of IEEE. Her area of interests is network security, data mining, cloud security and Biometrics.
OCR, text extraction, language translation, skew correction
In this work, a fast and robust document translation service is presented that makes use of both OCR and language translation functionalities. The entire service is semi-automated, thereby requiring minimum effort from the user.
The input image is first transferred from the user's phone to a high-performance computing system by means of Bluetooth technology. The image is fed into the application which makes use of a extraction algorithm that accurately extracts the document representing the ROI and further improves image quality using de-noising techniques. The processed image is fed into the Tesseract OCR engine for retrieval of English data and language translation capabilities of Google translate API is leveraged to efficiently translate the English text to Kannada.
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