Software Development Framework for Real-Time Face Detection and Recognition in Mobile Devices

Laxmisha Rai, Zhiyuan Wang, Amila Rodrigo, Zhaopeng Deng, Haiqing Liu


With the rapid use of Android OS in mobile devices and related products, face recognition technology is an essential feature, so that mobile devices have a strong personal identity authentication. In this paper, we propose Android based software development framework for real-time face detection and recognition using OpenCV library, which is applicable in several mobile applications. Initially, the Gaussian smoothing and gray-scale transformation algorithm is applied to preprocess the source image. Then, the Haar-like feature matching method is used to describe the characteristics of the operator and obtain the face characteristic value. Finally, the normalization method is used to match the recognition of face database. To achieve the face recognition in the Android platform, JNI (Java Native Interface) is used to call the local Open CV. The proposed system is tested in real-time in two different brands of smart phones, and results average success rate in both devices for face detection and recognition is 95% and 80% respectively.


Authentication, Image processing, Wearable, Framework, JNI, OpenCV, Personal identity, Smart phones

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International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
Creative Commons License
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