This paper presents sclera-based biometric recognition. The vessel patterns in sclera are different for every individual and this can be used to identify a person uniquely. In this analysis, we are using sobal filter and Otsu's thresholding methodology for sclera segmentation. Second we have designed a Gabor filter for sclera pattern enhancement to high light and binarize the sclera vessel patterns because the segmented sclera area is highly reflective. As a result, the sclera vascular patterns are unclear or/and have very low contrast. To accomplish the illumination impact and to achieve an illumination-invariant method, it is important to enhance the vascular patterns. Finally, we tend to plan a line-descriptor based feature extraction, registration, and matching technique. We have used the UBIRIS version one dataset for the experimentation of our analysis. The experimental results show that sclera recognition could be a trust worthy new biometrics for human identification

1. Abhijit Dasa, Umapada Palh, Miguel Angel Ferrer BallesterC and Michael Blumensteina"Sclera Recognition Using Dense-SIFT" 978-1-4799-3516-1/13/$31. 00 ©2013 IEEE
2. Khushhal Jindal, Kriti Gupta, Manan Jain, Manmohan Maheshwari"Bio-Medical Image Enhancement Based OnSpatial Domain Technique" ©2014 IEEE
3. Simona Crihalmeanu "On the use of multispectral conjunctival vasculature as a soft biometric" 978-1-4244-9497-2/10/$26. 00 ©2010 IEEE
4. Abhijit Dasa, Umapada Palb, Miguel Angel Ferrer Ballesterc and Michael Blumensteina" Fuzzy Logic Based Sclera Recognition" 978-1-4799-2072-3/14/$31. 00 ©2014 IEEE
5. Prateek Singh Sengar Tarun Kumar Rawat, Harish Parthasarathy "Color Image Enhancement by Scaling the Discrete Wavelet Transform
6. Coefficients" 978-1-4673-5149-2/13/$31. 00 ©2013 IEEEDi Zhu, Siyu Xia, Xin Zhou, Jihui Zheng "Hybrid Method for Human Eye Detection" 978-4799-3708-0/14/$31. 00c 2014 IEEE

Sclera Recognition Sclera Segmentation Pattern Recognition .