1. Lab 2: Fingerprints
CSE 402

2. Objective
Apply image processing techniques from previous lab to fingerprint images

3. Fingerprint image Our fingers have a pattern of ridges and valleys
We can compare the pattern of two fingers
If two patterns are similar enough, we mark them as a match
Separate lectures on fingerprints, this is only for lab exercise. Show what ridge ending & bifurcations are in the image.

4. binary Image We first binarize the image
There are only two values in the image (black and white)
Each pixel is marked as foreground (white) or background (black)
The foreground indicates the ridge structure

5. Ridge skeleton image
We convert a binary image to a ridge skeleton image
Each ridge in the binary image is shrunk to be 1 pixel wide
The ridge locations are recorded
Geometric and dimensional details of the ridges are ignored

6. Minutiae Points We are interested in 2 types of minutiae points
Ridge endings
Ridge bifurcations
We can detect these points with the ridge skeleton image
We can compare the location and orientation of these points to match images
Ridge
Ending
Bifurcation

7. Noise Images are not always “clean”
They are often corrupted by different types of noise
We will look at how “salt-and- pepper” noise can be reduced in an image

8. Image after Median Filtering
Noise Removal
Noisy Image
Image after Median Filtering

9. Noise Affects Minutiae detection
Minutiae from Noisy Image
Minutiae from Filtered Image
change color from green
Many spurious minutiae points