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An Introduction demo on
Mobile Camera Based Text Detection & Translation
Under The Guidance Of: Mrs. Hema N.
Presented By:...
Contents
 Introduction
 History
 Existing System
 Proposed System
 System Flow
 Requirement
 Block Diagram
 Test &...
Introduction…
Our project ‘Mobile camera based text detection and
translation’ retrieves text from an images and converts ...
Existing System
 In 1929, first OCR device was invented but it was mechanical device
 In about 1965, earliest form of OC...
Working…
 Capture image
 Detect edges
 Detect corners
 Match with stored image file
 Retrieve text from image
 Trans...
Working Diagram
Fig. a: Working diagram
6
System flow
 Algorithms:
 Edge detection
 Image feature filtering
 Image binarization
 Optical character recognition
...
Requirement
Mobile Hardware Requirements:
• ARM 11 processor or higher
• Memory 1 GB
• 256 MB RAM
• Mobile camera 3.2 mega...
Block Diagram
Captured
Image
Text Feature
Filtering
Google
APIs
File Library
Match
Image
Retrieve
Text
Translate
Text
Disp...
Example
Fig. c: Example
c.1 c.2
c.3 c.4
c.5
Fig c.1
Fig c.2
Fig c.3
Fig c.4
Fig c.5
10
Test & Results
Image quality :
As image quality degraded recognition rate will decrease
Recognition rate of character ‘A’ ...
Applications
Tourist understanding native language.
 Instant recognition of texts, street and e-mail addresses,
links, a...
Advantages
 Android Mobile OS based platform.
 No tiresome manual data entry.
 Versatility and ease of use.
 No databa...
Limitations
 Image taken by Mobile camera should be of good quality.
 Mobile should be of high specifications
 For tran...
Conclusion
This project which we want to implement is an Android
Mobile OS based application which is web based real time ...
Bibliography
1. Michael Hsueh “Interactive Text Recognition and Translation on a Mobile Device “
[Technical Report No. UCB...
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Word Detection & Translation from image on an android device

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Word Detection & Translation from image on an android device

  1. 1. An Introduction demo on Mobile Camera Based Text Detection & Translation Under The Guidance Of: Mrs. Hema N. Presented By: RITWIK KUMAR PRATEEK CHAUHAN
  2. 2. Contents  Introduction  History  Existing System  Proposed System  System Flow  Requirement  Block Diagram  Test & Results  Applications  Advantages & Limitation Conclusion Bibliography 2
  3. 3. 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. 3
  4. 4. 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. 4
  5. 5. Working…  Capture image  Detect edges  Detect corners  Match with stored image file  Retrieve text from image  Translate using Google API  Show Result 5
  6. 6. Working Diagram Fig. a: Working diagram 6
  7. 7. System flow  Algorithms:  Edge detection  Image feature filtering  Image binarization  Optical character recognition  Text correction  Text translation  Display of translation 7
  8. 8. Requirement Mobile 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 8
  9. 9. Block Diagram Captured Image Text Feature Filtering Google APIs File Library Match Image Retrieve Text Translate Text Display Output Text Fig. b: Block diagram 9
  10. 10. Example Fig. c: Example c.1 c.2 c.3 c.4 c.5 Fig c.1 Fig c.2 Fig c.3 Fig c.4 Fig c.5 10
  11. 11. Test & Results Image 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 11
  12. 12. 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. 12
  13. 13. Advantages  Android Mobile OS based platform.  No tiresome manual data entry.  Versatility and ease of use.  No database is needed  For data entry 13
  14. 14. 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. 14
  15. 15. 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. 15
  16. 16. Bibliography 1. 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 16

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