1. IMPLEMENTATION OF MOBILE
CAMERA BASED TEXT DETECTION
AND TRANSLATION
Mr. Vivek kumar
Computer Engineering, Pune University
Abstract— The overall capabilities of mobile devices have because text embedded in images and videos provides
rapidly increased in recent years in terms of processing power, important information.), Optical Character Recognition:
connectivity, and available sensors. These advancements, OCR, Optical Character Recognition, is developed to
together with the growing prevalence of smart phones, have translate scanned images of handwritten, typewritten or
made it feasible and in some cases preferable to run OCR printed text into machine-encoded text and Text Correction:
software on mobile platforms. The motivation of a real time text
The text correction is a necessary step after OCR text
translation mobile application is to help tourists navigate in a
recognition, since the result returned by the OCR engine is
foreign language environment. The application we have
not be always correct due to image imperfections. This type
implemented enables the users to get text translate as ease as a
of errors can be categorized into so called non-word error –
button click. The camera captures the text and returns the
translated result in real time. The system we implemented which means that the text string returned by OCR does not
includes automatic text detection, OCR (optical character correspond to any valid word in a given word set.
recognition) and text translation.
C. Proposed Work:
Introduction When, the user begins by capturing an image
containing text of interest using the Mobile camera. The
A. Relevance of the Work:
The advancements, together with the growing prevalence specified area of the image is processed on the device in
of smart phones, have made it feasible and preferable to run order to optimize it for transfer and input to the OCR Internet
OCR software on mobile platforms. The motivation of server / database. The processed data is sent to a web service
implementing this real time text translation mobile where recognition takes place. The results are delivered back
application is demo to help tourists navigate in a foreign to the device and a translated string is obtained
language environment (English) and overcome language
barriers. Even a giant OCR software manufacturer does not .D. Features:
provide text conversion to Hindi language. Smart phones with ARM (Advanced RISC
. Machine) processor used in mobile which is 32-
bit RISC microprocessor is used with 256 RAM in the
B. Present Theory and Practices: mobile which enable the process to be faster in mobile.
There are Prior and Related Work like text
extraction (Text extraction techniques are widely studied

2. The camera quality must be high for better accuracy 2. J2ME.
and the snap of the scripts must be taken in proper way that 3. J2EE.
the characters can be recognized.
Communications Interfaces
Stimulus/Response Sequences
 Capture the image 1. Mobile Internet (Runs fast on 3g Internet)
2. 2.1 Web browser inbuilt in Android Mobile OS
 Find text area
 Extract Lines
CONCLUSION
 Extract characters This project is an Android Mobile OS based
 Recognize Character application which is web based real time mobile
application for real-time text extraction, recognition and
 Match with image library
translation.
 Convert it to text
Now a day’s use of mobile is broadly increased and
 Translate using Google translator
almost each and every person possess mobile phone, in
 Display text in translated language which lots of applications run. Our project is also
compatible with mobile phones which make it portable
that’s a desired property of any software.
E. Technology & Programming Languages
Hence we can conclude this project is real time
User Interfaces
application and very useful for tourist navigation &
language understanding.
Our project has number of user interfaces that allow user to
access system easily. In this project guidelines and help files ACKNOWLEDGMENT
are given to user that is very useful to learn how to operate
software. Different buttons are provided to access these help. For the successful completion of any project, it takes
the complete dedication and the combined guidelines
Hardware Interfaces provided by college professors. The project would not have
been complete without the support, guidance and co-
1. Smart Mobile Phone with Advance RISC
operation of several persons to whom we owe our sincere
Microprocessor (ARM) 500MHz.
gratitude.
2. 5MP camera.
Firstly we are highly indebted to our class teacher
3. 256 RAM.
Prof. M.G. Bhandare. It was his genuine interest, timely
guidance and encouragement that has given us the
Software Interfaces
opportunity to put our ideas into reality and helped us to
1. Android Mobile operating System complete our project work successfully.

3. Had it not been the sincere efforts of our project
guide Prof. K.P.Gaikwad without whom it would have been [8] Ramakant Gaikwad, “Op-Amps and Linear Integrated Circuits”,
next to impossible for the completion of our project. His Prentice-Hall, 4th Edition
efforts have been very helpful in the development of project.
[9] Brian W. Kernighan, Dennis M. Ritchie, “The C programming
We are also very highly grateful to Prof. S.N.
Language”, Prentice-Hall, 1st Edition.
Kulkarni for his interest and encouragement in the progress
of our project. [10] Sing Li & Jonathan Knudsen, “Beginning J2ME: From Novice
Lastly we are highly indebted to all our respondents to Professional”, Prentice-Hall, 3rd Edition.
without whose co-operation the project would not have been
completed and the persons who have indirectly helped us.
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Federal Institute of Technology (ETH) Zurich 8092 Zurich,
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[3] Pradip Lamsal, “J2ME ARCHITECTURE AND RELATED
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