Sclera Feature Extraction Techniques

Sclera recognition becomes a research topic of many researchers in recent days. It's because of the uniqueness of the blood vessels in the sclera as well the easily accessible of the features i.e No user co-operation is needed. Since there are few challenges like distance of capturing, angle of capturing, Lighting, different poses of human, movability of eyes, wetness of eye, multilayered structure of eyes and etc. The vessel patterns are treated as patterns to recognize the individuals and it has been extracted. Feature extraction plays a major role among the various steps of sclera recognition. There are numerous types of features are extracted from the sclera using different types of approaches. In this paper, we propose a different feature extraction method and its efficiency in terms of accuracy in sclera recognitions. In this we have discuss the methods of Hu's invariant moments, Minutiae, CDF, Affine Transform, Line segment descriptor, Angular grid, LBP, D-SIFT, Harris corner and edge detection, DWT co-efficient, LDP. The comparative analysis of the various methods has been tabulated and explained with its effectiveness.