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Proceedings Paper

Face verification system for Android mobile devices using histogram based features
Author(s): Sho Sato; Kazuhiro Kobayashi; Qiu Chen
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Paper Abstract

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

Paper Details

Date Published: 11 July 2016
PDF: 8 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110D (11 July 2016); doi: 10.1117/12.2243581
Show Author Affiliations
Sho Sato, Kogakuin Univ. (Japan)
Kazuhiro Kobayashi, Kogakuin Univ. (Japan)
Qiu Chen, Kogakuin Univ. (Japan)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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