Open AccessAssimilating region of interest for fused biometric modalities through cie l*a*b* color space
Author(s) -
P. Bhargavi Devi,
K. Sharmila
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1085/1/012004
Subject(s) - biometrics , modalities , modality (human–computer interaction) , fingerprint (computing) , computer science , hand geometry , identification (biology) , artificial intelligence , computer vision , pixel , iris recognition , pattern recognition (psychology) , social science , botany , sociology , biology
Idiosyncrasy in recent times has been a challenge that is not quite easily effectuated in many domains and work structures. Security compromises have led to immeasurable loss and altered the deportment of individuals. In order to counter such circumstances, biometric modality analysis and utilization stimulate an inimitable framework to enhancement of security mitigated impostures. Nonetheless, the existing indagation has always instituted the single biometric modality processing and evaluation. Although the previous work of pre-processing and post-processing for biometric modalities such as fingerprint, iris, gait, and other physiological and behavioral modalities have been considered through explicit algorithmic and computational processing, the rate of precision fallacy and contriving unique identification has been a lingering question. This paper focuses on augmenting the efficacy of identification through the fused biometric modalities of fingerprint and iris, along with unsheathing the region of interest (ROI) by designating color masks using the CIE L*a*b* color space and delta disparity computation. The histogram analysis is implemented to analyze the pixel intensity, and the pixel matched extraction is surface plotted using MATLAB.