The Potential of Using Brain Images for Authentication

Abstract

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Recent developments in investigation on buckling and post buckling responses of laminated composite shells

“…Analysis of composite shell is carried out by applying the compressive load at the ends of the structure based on the application, there by the deformation/deflection taken place in the geometry. Then the load is increased to find the materials capability or the stability to withstand further loads after the buckling and load carrying capacity until all the layers of the laminate fails . The summarized data on the various research works buckling analysis and post‐buckling analysis of shell structures is presented with the relationship between the geometries/configurations and the loadings under different environments are shown in Table .…”

Brain-printing biometrics underlying mechanism as an early diagnostic technique for Alzheimer's disease neurodegenerative type

“…The onset of AD typically correlates with the overexpression of Aβ in brain tissue ( Bae and Yi, 2020 ; Calabrò et al, 2021 ). At this early stage, the profound structural changes that occur can be correlated with the BPB technique which would be designed to generate personalized IDs using both computerized brain structural analysis as well as brain activity via sMRI ( Chen et al, 2014 ) and EEG intra-connected devices, respectively ( Jackson and Snyder, 2008 ). The current review highlights the idea that AD can be characterized and diagnosed by monitoring the early morphological and structural changes developed during the preclinical stage using the BPB technique.…”

“…1 ). sMRI is used for deep brain image scanning to identify the onset of brain deformities and associated unique hidden brain structural changes before or as the disease precipitates, including the surface area of brain, white/gray matter volume, cortical-subcortical folds, and brain gyrification index ( Aloui et al, 2012 ; Chen et al, 2014 ; Fujita and Hagiwara, 2019 ) ( Fig. 1 ).…”