• Priyanka Kulkarni
• Dr. Sarika solanke

Out of many available biometric identification methods, iris recognition seems to be promising and most accurate method. The reason is iris structure remains unchanged throughout one's lifetime. One of the live applications of this is: over 1000 ATMs of financial institutions in Chicago and Montreal are now using iris recognition in lieu of debit cards. Imagine the situation if iris recognition systems/scans used in ATMs are fooled or spoofed. Financial system will break with a huge damage. To avoid this, there must exist technique(s) to determine if iris recognition methods are being bypassed. This paper presents an in-depth analysis of the effect of contact lens on iris recognition performance. We also present the IIIT-D Contact Lens Iris database with over 6500 images pertaining to 101 subjects. For each subject, images are captured without lens, transparent (prescription) lens, and color cosmetic lens (textured) using two different iris sensors. Weber Local Descriptor (WLD) is proposed in this paper for feature extraction in contact lenses detection. Also, the results are compared with Binarized Statistical Image Feature (BSIF) analysis which shows that WLD gives favorable results. We organize WLD features to compute a histogram by encoding both differential excitations and orientations at certain locations. This method focuses on different properties of a pixel of iris image and thus, it provides more accurate results than other techniques.

Iris Recognition, Retina, SVM, Biometric, Segmentation, Contact lenses

"Textured Contact Lenses Detection in Iris Recognition Using Weber Local Descriptor (WLD)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 12, page no.642-649, December 2019, Available :http://www.jetir.org/papers/JETIR1908093.pdf

"Textured Contact Lenses Detection in Iris Recognition Using Weber Local Descriptor (WLD)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 12, page no. pp642-649, December 2019, Available at : http://www.jetir.org/papers/JETIR1908093.pdf