LBPV for Newborn Personal Recognition System

An increased anxiety in security in modern ages has primarily resulted in vast attention being given to biometric-based authentication techniques. Biometrics refers to the automatic authentication of human beings based on their physiological and/or behavioral characteristics. This paper proposes a newborn footprint matching system based on the extraction of texture features using LBP. Newborn and infant footprint based individual authentication is a critical issue where multiple births occur, birthing centers, hospitals, which is an understudied problem. This study proposes a novel online newborn personal authentication system based on baby footprint authentication. The proposed system can authenticate the digital footprint images with lowresolution. In comparison to the prevailing systems, our online newborn footprint authentication systems employ low-resolution footprint images to accomplish effective personal authentication. The novel newborn authentication system comprises of two parts: an image acquisition and a proficient algorithm for fast newborn footprint authentication. A robust ROI extraction method is defined. The features are extracted using Local Binary Pattern system for newborn footprint and the images are classified using Support Vector Machine and Global Matching K-NN. The investigation results exhibit the feasibility of the proposed system.