This document summarizes a fingerprint post processing algorithm that performs minutia extraction and false minutia removal. It first describes preprocessing steps including binarization, orientation estimation, and thinning. It then outlines the minutia detection process which uses a rotation mask method and crossing number algorithm to identify bifurcations and terminations. Finally, it details a false minutia removal process that compares local patches around detected minutia to templates to identify and remove minutia located on image edges or in close proximity, which are likely false detections.

1. FINGERPRINT POST PROCESSING
minutia extraction and false minutia removal
M.IMRAN BAIG EE083050
KHAWAR HAYAT EE083069
ABID ALI EE083103

2. Given images
• Binary image
• Orientation
• Mask
• Thinned image

3. Algorithm
• Rotation mask method
• Crossing number algorithm

4. Rotation mask method
0 1 0
0 1 0
0 0 0
1 0 1
0 1 0
0 1 0
Rotate mask 45 degree and compare with the image

5. Minutia Detection

 
8
1
191 |,|5.0
i
ii PPPPCN

6. Minutia Detection Cont’d
0 1 0
0 1 0
0 0 0
1 0 1
0 1 0
0 1 0
Bifurcation
=ABS((0-0)+(0-1)+(1-0)+(0-0)+(0-1)+(1-0)+(0-
1)+(1-0))
=6
Minutia termination
=ABS((0-0)+(0-0)+(0-0)+(0-0)+(0-0)+ (0-1)+(1-
0)+(0-0))
=2

7. Minutia Detection Cont’d

8. False Minutia Removal
• Create an image of minutia
• Take a chunk around a minutia point
• Compare that image with given mask image
• If these are at the edge then remove that
minutia

9. False Minutia Removal Cont’d
0 1 1
1 0 1
1 1 1
1 0 0
1 0 0
1 0 0
0 0 0
1 0 0
1 0 0
0 1 1
1 0 1
1 1 1
1 1 1
1 1 1
1 1 1
0 1 1
1 0 1
1 1 1
Minutia in image sum=7 * Mask output sum=2
Minutia in image sum=7 * Mask output sum=7

10. False Minutia Removal Cont’d

11. False Minutia Removal Cont’d
• Now remove these pattern

12. False Minutia Removal Cont’d
• Take an array, size is nearly equal to distance
between two lines. We take25x25 because
distance between lines is around 14 pixel.
• Find the minutia and take a chunk of 25x25.
• If there is minutia within this window then
remove both minutia.
• If there is bifurcation then remove the
termination and bifurcation because it is a
spike.

13. False Minutia Removal Cont’d
1
1
1
1
1
1
1
1 1
1 1
1 1
1
1 1
1

14. False Minutia Removal Cont’d
• Like we take window around the termination
we also take the window around the
bifurcation
• Find if there is more than one bifurcation
within the window remove both bifurcation
because it is hole.

15. False Minutia Removal Cont’d
1
1
1
1 1 1
1
1
1
1
1
1 1 1
1 1
1 1
1 1 1
1

16. False Minutia Removal Cont’d
1
1
1
1
1
2
1
1
1
3

17. False Minutia Removal Cont’d
1 1
1 1
1
1
1
1 1
1
1 1
1 1
1 1
1
1
1
1 1
1 1
1 1

18. False Minutia Removal Cont’d

19. References
• Rohit Singh , Utkarsh Shah , Vinay Gupta
Indian Institute of technology, Kanpur
• Fingerprint Image Enhancement and Minutiae
Extraction, Raymond Thai, The University of
Western Australia

20. THANK YOU