1. Fingerprint Analysis (part 2) Pavel Mrázek

2. Local ridge frequency

4. Image enhancement / binarization General rule: –Smooth along ridges –Enhance ridge-valley contrast –Separate fingerprint from background (segmentation) Various methods: –Convolution –PDEs –Morphology –Gabor filters –…

5. Gabor filters Several orientations Several frequencies At each position, –select orientation –select frequency –filter using the appropriate Gabor filter

6. Gabor filters

7. Coherence enhancing shock filter Shock filter: Regularized:

8. Coherence enhancing shock filter Use direction estimate: w … dominant eigenvector of the structure tensor

9. Examples Coherence enhancing shock filter

10. Ridge thinning Thinning: morphological operation Pixel value set to background if ridge connectivity not affected Structuring element: typically 3x3 window 9 pixels, 512 possible configurations, look-up

11. Singular point detection Methods for core and delta detection: –Poincaré index –Irregularity of orientation field, curvature –Partitioning of orientation field Reliability problems

12. Texture features

13. Feature extraction summary Extract features, store a template Prepare representation useful for matching –minutiae –… Reduce memory requirements (typical size 500 B – 30 kB) Privacy: fingerprint not stored

14. Enrollment Register user, store data into a database

15. Verification Compare to enrolled template, accept / reject a match

16. Identification Recover identity, 1-to-N match

17. References Maltoni et al.: Handbook of Fingerprint Recognition. Springer 2003. Maltoni. A tutorial on fingerprint recognition. In LNCS 3161, Springer 2005. Hong, Wan, Jain. Fingerprint image enhancement: algorithm and performance evaluation. IEEE PAMI 1998. Zhou, Gu. A model-based method for the computation of fingerprints’ orientation field. IEEE TIP 2004. Weickert. Coherence enhancing shock filters. DAGM 2003. Contact: mrazekp -at- cmp.felk.cvut.cz