1. Android QR-Code Detection Cerman Martin, 0625040 mcerman@prip.tuwien.ac.at

2. Content  Topic & Challenges (original proposal)  IDE‘s, Languages & Libraries  Chosen Approach  Outlier Filtering  Tuneable Parameters  TODO (original proposal / what was achieved)  Topic & Challenges (what was achieved)  Live Demonstration Android QR-Code Detection, Cerman Martin, 06250402

3. Topic & Challenges (original proposal)  Detect and read QR-Codes on an Android Phone  As defined by the ISO/IEC Standart „Set of black squares on a white background“ Various sizes (Version 1-40) Android QR-Code Detection, Cerman Martin, 06250403 Topic  Detection under various lighting conditions  Perspective distortion  Detection of QR-Code size  Real-Time Challenges / Goals

4. IDE‘s, Languages & Libraries Android QR-Code Detection, Cerman Martin, 06250404  MATLAB  Eclipse ADT (Android Development Toolkit) CDT (C++ Development Toolkit) NDK (Android Native Development Kit)  Visual Studio 2012 OpenCV Library

5. Chosen Approach Android QR-Code Detection, Cerman Martin, 06250405  „Fast Radial Symmetry for Detecting Points of Interest“, [1]  Algorithm Transform to grayscale and reduce image size Determine gradient in x and y direction Compute orientation and magnitude image Compute symmetry image at certain radii Smooth using a Gauss kernel Non-maximum suppression

6. Chosen Approach (transform to grayscale) Android QR-Code Detection, Cerman Martin, 06250406

7. Chosen Approach (x derivative) Android QR-Code Detection, Cerman Martin, 06250407

8. Chosen Approach (y derivative) Android QR-Code Detection, Cerman Martin, 06250408

9. Chosen Approach (orientation image) Android QR-Code Detection, Cerman Martin, 06250409

10. Chosen Approach (magnitude image) Android QR-Code Detection, Cerman Martin, 062504010

11. Chosen Approach (symmetry image) Android QR-Code Detection, Cerman Martin, 062504011

12. Chosen Approach (thresholded symmetry image) Android QR-Code Detection, Cerman Martin, 062504012

13. Outlier Filtering Android QR-Code Detection, Cerman Martin, 062504013  Maximal number of outliers is around 20  Algorithm Build a complete graph Compute for each vertex distances to all other vertices Compute angle for each vertex trio Filter outliers by setting restrictions on maximal angle deviation and distance difference for each vertex trio  Turned out to work very well

14. Tuneable Parameters Android QR-Code Detection, Cerman Martin, 062504014  Feature Detection Image reduction factor Search radius Minimal number of positively affecting pixels Symmetry strength  Outlier Filtering Maximal edge length difference of each vertex trio Maximal angle deviation of each vertex trio  Frame Management Split up searching (different scales) and filtering among frames

15. TODO (original proposal) Android QR-Code Detection, Cerman Martin, 062504015  Determine parameters Image size Radii  Filter outliers Based on neighborhood Find suitable feature descriptor  QR-Code reading

16. TODO (what was achieved) Android QR-Code Detection, Cerman Martin, 062504016  Determine parameters Image size Radii  Filter outliers Based on neighborhood Find suitable feature descriptor  QR-Code reading

17. Topic & Challenges (what was achieved)  Detect and read QR-Codes on an Android Phone  As defined by the ISO/IEC Standart „Set of black squares on a white background“ Various sizes (Version 1-40) Android QR-Code Detection, Cerman Martin, 062504017 Topic  Detection under various lighting conditions  Perspective distortion  Detection of QR-Code size  Real-Time Challenges / Goals /

18. Live Demonstration 18your title

19. References Android QR-Code Detection, Cerman Martin, 062504019  [1] Fast Radial Symmetry for Detecting Points of Interest, G. Loy and A. Zelinsky, IEEE Transactions on Pattern Analysis and Machine Intelligence, August 2003

20. Thank you