An Adaptive and Viable Face Identification for Android Mobile Devices
Smartphones apart from enjoying access to personal data, are increasingly being used for performing sensitive and critical financial transactions. Thus, making smartphones vulnerable to numerous contemporary threats as strong security solutions were not developed while considering resource-constrained devices like mobile phones in mind. A need for such a security solution persists that is capable of delivering strong security without compromising user convenience. Biometric tends to offer unparalleled user convenience. Although sparse usage of the face and fingerprint biometrics appear on mobile phone devices. However, their application is limited to mere device unlocking. The low accuracy offered by such solutions results in low user acceptance and limits their use in other security solutions. Therefore, it is evident that the recognition accuracy has to be inspected and improved to deal with the real-world situations. In this chapter, an adaptive face identification capable of minimizing the variations of real-world uncontrollable situations has been developed primarily on Android mobile devices while investigating the state of art algorithms in the field of face identification; Face Detection: Haar detector, Local Binary Patterns (LBP) detector; Face Identification: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Patterns Histograms (LBPH).
KeywordsAndroid Biometrics Face identification Password Security
This work was partially supported by Ministry of Higher Education Malaysia (Kementerian Pendidikan Tinggi) under Research Initiative Grant Scheme number: RIGS16-334-0498.
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