Enhancement of Authentication Performance based on Multimodal Biometrics for Android Platform

Abstract

In this research, we have explored personal authentication system through multimodal biometrics for mobile computing environment. We have selected face and speaker recognition for the implementation of multimodal biometrics system. For face recognition part, we detect the face with Modified Census Transform (MCT). Detected face is pre-processed through eye detection module based on k-means algorithm. Then we recognize the face with Principal Component Analysis (PCA) algorithm. For speaker recognition part, we extract features using the end-point of voice and the Mel Frequency Cepstral Coefficient (MFCC). Then we verify the speaker through Dynamic Time Warping (DTW) algorithm.Our proposed multimodal biometrics system shows improved verification rate through combining two different biometrics described above. We implement our proposed system based on Android environment using Galaxy S hoppin. Proposed system presents reduced false acceptance ratio (FAR) of 1.8% which shows improvement from single biometrics system using the face and the voice (presents 4.6% and 6.7% respectively).

A Study on the Physical Input Method of Future Display

“…종이와 같이 가벼우면서도 얇고 [5], 유연한 재료를 사용해 [6] 고정형 스크린이 갖는 한계를 극 복하고 새로운 폼팩터의 특징을 가지고 있는 [7] 플렉서블 디스플레이(Flexible Display)는 형태 변 형에도 특성의 손실 없이 제 기능을 발휘할 수 있으며, 커브드(Curved), 벤더블(Bendable), 폴더블 (Foldable), 롤러블(Rollable), 스트레처블(Strechable)이 이에 속한다 [8]…”