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Face Verification System for Android Mobile Devices Using Histogram Based Features

机译:使用基于直方图的功能的Android移动设备的面部验证系统

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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.
机译:本文提出了一种可在Android移动设备上运行的人脸验证系统。在该系统中,首先通过Android设备上的内置摄像头捕获面部图像,然后使用类似Haar的功能和AdaBoost学习算法来实现面部检测。所提出的系统使用基于直方图的特征来验证检测到的面部,该特征是由低频域中使用DCT系数的二进制矢量量化(VQ)直方图以及空间域中的改进局部二进制模式(Improved LBP)直方图生成的。首先分别获得具有不同类型直方图特征的验证结果,然后通过加权平均进行组合。我们通过使用公开可用的ORL数据库和Android平板电脑捕获的面部图像来评估我们提出的算法。

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