word detection & translation from image on an android device
DESCRIPTION
TRANSCRIPT
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An Introduction demo on
Mobile Camera Based Text Detection & Translation
Under The Guidance Of: Mrs. Hema N.
Presented By: RITWIK KUMAR
PRATEEK CHAUHAN
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Contents
Introduction History Existing System Proposed System System Flow Requirement Block Diagram Test & Results Applications Advantages & LimitationConclusionBibliography
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Introduction…
Our project ‘Mobile camera based text detection and translation’ retrieves text from an images and converts it into text format, then it is translated to specified language.
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Existing System
In 1929, first OCR device was invented but it was mechanical device
In about 1965, earliest form of OCR was implemented in one of the first generation computers for Airline Ticket stock.
Revolutionary in 1971, it was implemented in postal services OCR systems where reading and printing of routing bar code was done on the postal code.
In 1974, the modifications was done which would allow blind people to have a computer read text to them out loud.
In late 90’s, Webcam was used for OCR process.
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Working…
Capture image
Detect edges
Detect corners
Match with stored image file
Retrieve text from image
Translate using Google API
Show Result
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Working Diagram
Fig. a: Working diagram
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System flow
Algorithms:
Edge detection
Image feature filtering
Image binarization
Optical character recognition
Text correction
Text translation
Display of translation
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RequirementMobile Hardware Requirements:• ARM 11 processor or higher• Memory 1 GB • 256 MB RAM• Mobile camera 3.2 mega pixel and above
Software Requirements:• Operating System – Android Mob OS 2.2+• Windows 7 OS• Mat lab OCR,ADT bundles Communication Requirements:• Internet Connection is required• Android Mobile OS inbuilt web browser
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Block Diagram
Captured Image
Text Feature Filtering
Google APIs
File Library
Match Image
Retrieve Text
Translate Text
Display Output Text
Fig. b: Block diagram
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Example
Fig. c: Example
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Fig c.1Fig c.2Fig c.3Fig c.4Fig c.5
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Test & ResultsImage quality :
As image quality degraded recognition rate will decrease
Recognition rate of character ‘A’ , ‘B’ , ‘L’ will be higher than recognition rate of character ‘y’ , ‘u’ , ‘c’.
Fig. d: Test & result
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Applications
Tourist understanding native language.
Instant recognition of texts, street and e-mail addresses, links, and telephone numbers.
Unknown language guideline.
Easy to recognize road signs scripts.
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Advantages
Android Mobile OS based platform.
No tiresome manual data entry.
Versatility and ease of use.
No database is needed
For data entry
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Limitations
Image taken by Mobile camera should be of good quality.
Mobile should be of high specifications
For translation of extracted text , Internet connection is required.
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Conclusion
This project which we want to implement is an Android Mobile OS based application which is web based real time mobile application for real-time text extraction, recognition and translation.
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Bibliography1. Michael Hsueh “Interactive Text Recognition and Translation on a Mobile Device “
[Technical Report No. UCB/EECS-2011-57 ]
2. Yassin M.Y.Hasan and Lina J.Karam “Morphological Text Extraction from Images” IEEE Transaction on Image Processing Vol.9 No.11, Nov 2000
3. Nobuyuki Otsu, A threshold selection method from gray-level histograms. IEEE Trans.Sys.,Man., Cyber 9(1):62-66
4. Celine Mancas-Thillou, Bernard Gosselin, Color text extraction with selective metric based clustering. Computer Vision and Image Understanding 2007
5. B. Epshtein, Detecting Text in Natural Scenes with Stroke Width Transform. Image Rochester NY, pp. 1-8.
6. Derek Ma , Qiuhau Lin, Tong Zhang “Mobile Camera Based Text Detection and Translation” – research paper
7. WWW.wikipedia.org/optical_character_recognization