Title :
Application of pyramidal directional filters for biometric identification using conjunctival vasculature patterns
Author :
Tankasala, Sriram Pavan ; Doynov, P. ; Derakhshani, R.
Author_Institution :
Dept. of Comput. Sci. Electr. Eng., Univ. of Missouri - Kansas City, Kansas City, MO, USA
Abstract :
Directional pyramidal filter banks as feature extractors for ocular vascular biometrics are proposed. Apart from the red, green, and blue (RGB) format, we analyze the significance of using HSV, YCbCr, and layer combinations (R+Cr)/2, (G+Cr)/2, (B+Cr)/2. For classification, Linear Discriminant Analysis (LDA) is used. We outline the advantages of a Contourlet transform implementation for eye vein biometrics, based on vascular patterns seen on the white of the eye. The performance of the proposed algorithm is evaluated using Receiver Operating Characteristic (ROC) curves. Area under the curve (AUC), equal error rate (EER), and decidability values are used as performance metrics. The dataset consists of more than 1600 still images and video frames acquired in two separate sessions from 40 subjects. All images were captured from a distance of 5 feet using a DSLR camera with an attached white LED light source. We evaluate and discuss the results of cross matching features extracted from still images and video recordings of conjunctival vasculature patterns. The best AUC value of 0.9999 with an EER of 0.064% resulted from using Cb layer in YCbCr color space. The best (lowest value) EER of 0.032% was obtained with an AUC value of 0.9998 using the green layer of the RGB images.
Keywords :
blood vessels; channel bank filters; decidability; feature extraction; image classification; image colour analysis; iris recognition; sensitivity analysis; AUC value; B+Cr-2 layer combination; DSLR camera; EER; G+Cr-2 layer combination; HSV; LDA; R+Cr-2 layer combination; RGB format; RGB image; ROC curve; YCbCr color space; area under the curve; conjunctival vasculature pattern; contourlet transform implementation; cross matching feature extraction; decidability value; directional pyramidal filter bank; equal error rate; eye vein biometrics; linear discriminant analysis; ocular vascular biometric identification; receiver operating characteristic curve; red green and blue format; still images; video frames; white LED light source; Cameras; Density measurement; Feature extraction; Filter banks; Image color analysis; Image segmentation; Transforms; Contourlet transform; Pyramidal directional filter banks; biometrics; conjunctival vasculature patterns; vein recognition;
Conference_Titel :
Technologies for Homeland Security (HST), 2013 IEEE International Conference on
Conference_Location :
Waltham, MA
Print_ISBN :
978-1-4799-3963-3
DOI :
10.1109/THS.2013.6699079