Performance Assessment of Color Spaces in Multimodal Biometric Identification with Iris and Palmprint using Thepade‟s Sorted Ternary Block Truncation Coding

Biometrics refers to the automatic identification of an individual based on his/her physiological and behavioral traits. Multimodal person authentication system is more effective and more challenging. The fusion of multiple biometric traits helps to minimize the system error rate. Here Iris and Palmprint fusion at Matching Score level is performed. The feature extraction in spatial domain using Thepade’s sorted ternary block truncation coding (TSTBTC) using level 2 is taken here to reduce the feature vector size of biometric traits. Iris and Palmprint are together taken here to improve accuracy in terms of genuine acceptance ratio (GAR) in Multimodal Biometric identification. The test beds of 60 pairs of Iris and Palmprint samples of 10 person (6 per person of iris as well as Palmprint) are used as test bed for experimentation. In this Paper different color spaces are considered on iris images for improvement in genuine acceptance ratio (GAR). Experimental results consider different matching score proportion of Iris: Palmprint. Using propose techniques with Iris: Palmprint Score 1:3 using TSTBTC Level2 given better performance as indicated by higher GAR values than all other considers scores. RGB color spaces for multimodal fusion of iris: palmprint gives high GAR than all other color spaces like YCgCb, YIQ, YCbCr, YIQ, and KLUV. Keyword-Multimodal Biometric, Matching Score level fusion, GAR, TSTBTC.