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RESEARCH AND IMPLEMENTATION OF FACE RECOGNITION ALGORITHM BASED ON ANDROID PLATFORM

机译:基于ANDROID平台的人脸识别算法研究与实现

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With the rapid development of the application of face recognition technology, the application of the combination of human and identification is becoming more and more extensive. In view of the fact that most of the current face recognition technologies are based on computers, the scope of use is limited, and the development cost is high. This article analyzes and studies the face detection and face recognition algorithms. In order to improve the detection speed and reduce the complexity of the algorithm, this article combines skin color segmentation and Adaboost algorithm Optimization: Pre-judge the position of the face based on the principle of skin color segmentation to determine the region of interest, avoid extracting the entire picture for face detection, and achieve the purpose of reducing the time for facial feature extraction. The experimental results show that the detection speed of the combination optimization algorithm based on skin color-Adaboost is faster than before Adaboost optimization. Finally, the face recognition is realized on the Android platform based on the PCA face recognition algorithm, and the recognition rate can reach 97.4%. The results show that the operation of the whole system of human identification and identification does not exceed 2s, which meets the real-time nature of terminal applications.
机译:随着人脸识别技术应用的迅速发展,人与身份识别相结合的应用越来越广泛。鉴于目前大多数人脸识别技术都是基于计算机的,使用范围有限,开发成本高。本文对人脸检测和人脸识别算法进行了分析和研究。为了提高检测速度,降低算法复杂度,本文结合肤色分割和Adaboost算法优化:根据肤色分割原理预先判断人脸位置,确定感兴趣区域,避免提取整张图片进行人脸检测,从而达到减少人脸特征提取时间的目的。实验结果表明,基于肤色Adaboost的组合优化算法的检测速度比Adaboost优化前快。最后,基于PCA人脸识别算法在Android平台上实现了人脸识别,识别率可达97.4%。结果表明,整个人体识别识别系统的运行时间不超过2秒,满足终端应用的实时性。

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