1. Centrality Bias Measure for High Density QR Code Module Recognition
Source: Signal Processing: Image Communication, Vol. 41, pp , 2016.
Authors: I. Tkachenko, W. Puech, O. Strauss, J.-M. Gaudin, C. Destruel, and C. Guichard
Speaker: Huang Peng-Cheng
Date: 11/28/2018

2. Outline Introduction Proposed centrality bias measure
Recognition methods using WMSE measure
Experimental results
Conclusions

3. Introduction(1/4)

4. Introduction (2/4)

5. Introduction(3/4)

6. Introduction(4/4)

7. Proposed centrality bias measure(1/2)
The Weighted Mean Square Error (WMSE)measure
N is the total number of weights used in these calculations.

8. Proposed centrality bias measure(2/2)

9. Recognition methods using WMSE measure(1/2)
Second step – recognition based on module characterization
First step – module classification

11. Experimental results(1/5)
--Recognition results

12. Experimental results (2/5)
--Recognition results

13. Experimental results (3/5)
--Recognition results

14. Experimental results (4/5)
--Recognition results

15. Experimental results(5/5) --Weight parameter (K) optimization

16. Conclusions
All proposed methods improved the recognition results by up to 5%
The minimal recognition rate with our methods is 93%