Abstract
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.
Highlights
In the recent years, devices running on Android platform, and smart phones are becoming increasingly ubiquitous
Most of the earlier works related to Android, face recognition, and emotion recognition etc., are fail to generalize the approach towards developing Android based software framework for face recognition, which can be applied to several applications and devices for the privacy protection, user security, user authentication, and fraud detection
The Haar more inclined to face detection, SIFT and SURF are more complicated than Haar, the Haar feature algorithm is used for face recognition in this paper
Summary
Devices running on Android platform, and smart phones are becoming increasingly ubiquitous. Most of the earlier works related to Android, face recognition, and emotion recognition etc., are fail to generalize the approach towards developing Android based software framework for face recognition, which can be applied to several applications and devices for the privacy protection, user security, user authentication, and fraud detection. Considering these developments, in this paper, we explore the tools and methods necessary for implementing generalized Android based software development framework for real-time face detection and recognition in mobile applications.
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