【摘要】：隨著智能化信息處理技術(shù)的不斷發(fā)展,人臉識別已成為身份認證領(lǐng)域的主要研究方向,并廣泛應(yīng)用于人們的日常生活。傳統(tǒng)的人臉識別系統(tǒng)以電腦為平臺,體積大,使用不靈活,而嵌入式ARM平臺具有體積小、低功耗、高性能、低成本的特點,因此基于ARM平臺開發(fā)人臉識別系統(tǒng)具有重要的應(yīng)用價值。本文設(shè)計實現(xiàn)了一種穩(wěn)定、準(zhǔn)確的嵌入式人臉識別系統(tǒng)。首先,系統(tǒng)采用基于Crotex-A9架構(gòu)的三星Exynos 4412開發(fā)板作為嵌入式ARM的開發(fā)平臺,在此平臺上完成了嵌入式Linux操作系統(tǒng)、Qt圖像化界面和OpenCV計算機視覺庫的移植。其次,深入分析并實現(xiàn)了基于Adaboost算法的人臉檢測;實現(xiàn)并對比了基于Eigenfaces、Fisherfaces和LBPH三種算法的人臉識別;通過深入研究人臉圖像預(yù)處理方法,從而進一步提高了識別性能。最后,本文設(shè)計出完整的嵌入式人臉識別系統(tǒng),實現(xiàn)了基于USB攝像頭的視頻采集顯示和人臉識別功能,并測試了系統(tǒng)四個功能模塊,包括人臉庫的建立、特征庫的訓(xùn)練、導(dǎo)入配置文件和人臉識別。系統(tǒng)設(shè)計完成后,本文測試了系統(tǒng)的識別率和運行速度等性能指標(biāo)。整個系統(tǒng)的測試結(jié)果表明本文設(shè)計的人臉識別系統(tǒng)具有較完備的功能、友好的界面、便捷的使用、高效的識別效果。
[Abstract]:With the development of intelligent information processing technology, face recognition has become the main research direction in the field of identity authentication, and widely used in people's daily life. The traditional face recognition system takes computer as the platform, the volume is large, the use is inflexible, and the embedded ARM platform has the characteristics of small size, low power consumption, high performance and low cost. Therefore, the development of face recognition system based on ARM platform has important application value. A stable and accurate embedded face recognition system is designed and implemented in this paper. Firstly, the system adopts Samsung Exynos 4412 development board based on Crotex-A9 architecture as the development platform of embedded ARM. On this platform, the embedded Linux operating system, Qt image interface and OpenCV computer visual library are transplanted. Secondly, in-depth analysis and implementation of face detection based on Adaboost algorithm; achieve and compare the three algorithms based on Eigenfaces,Fisherfaces and LBPH face recognition; through in-depth study of face image preprocessing methods, so as to further improve the recognition performance. Finally, this paper designs a complete embedded face recognition system, realizes the functions of video capture and display and face recognition based on USB camera, and tests the four functional modules of the system, including the establishment of human face database and the training of feature base. Import configuration files and face recognition. After the design of the system, the recognition rate and running speed of the system are tested. The test results of the whole system show that the face recognition system designed in this paper has more complete function, friendly interface, convenient use and high efficiency recognition effect.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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