1. SIRISHA SUMANTH and LATIF ALIANTO
IRIS DETECTION
SIRISHA SUMANTH
and
LATIF ALIANTO

2. The Iris as a Biometric Why Iris? Data-rich physical structure
- The tabecular meshwork
The cornea – protection
Stability of the iris pattern
Non-invasive method
Genetic independence

3. Preprocessing Image acquisition - Focus on high resolution and quality
- Moderate illumination
- Elimination of artifacts
Image localization
Adjustments for imaging contrast, illumination and camera gain

4. Iris Isolation Removal of parts other than the iris - Circular mask
Image cropping
- Use of the geometry of the eye
- Reduction in image size

5. Feature Extraction Pattern of the tabecular network
Comparison of edge operators
LoG operator
- Calculates second spatial derivative of an image
- Not affected by noise due to smoothing operation
- Isotropic operator

6. Extraction Process
 

7. Respone of LoG to a step edge

8. Discrete approximation of LoG function ( σ= 1.4)

9. Database creation and data compression
Efficient use of storage space
Edge information is stored in a binary image – use of ones and zeros only
Majority of the data are zeros
Further compression using the run length of zeros
Compression of KB to KB

10. Data Validation Test of statistical independence
Parameter – Hamming distance
- gives a measure of the disagreement
Hamming distance = zero =>identity validated
Hamming distance ≠ zero =>invalid ID

11. Images of different irises

12. Results Database Iris 1 Iris 2 Iris 3 Iris 4 Iris 5 Iris 6 Iris 7
8824
9005
8983
9349
9211
8788
9053
9082
7371
7767
7883
7625
6924
7319
7524
7886
8212
7800
7115
7504
7679
8368
8190
7329
7950
7951
8458
7555
8188
8455
7469
7740
8059
7069
7450
7693