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题名: 移动环境下的人脸识别系统研究
其他题名: Research of Face Recognition System in Mobile Environment
作者: 鄂生强
导师: 南琳
分类号: TP391.41
关键词: 人脸识别 ; 人脸检测 ; 人眼检测 ; 图像归一化 ; 局部二值模式
索取号: TP391.41/E29/2012
学位专业: 计算机应用技术
学位类别: 硕士
答辩日期: 2012-05-28
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 信息服务与智能控制技术研究室
中文摘要: 近年来,随着公众对信息安全重视程度的逐渐加深,传统的基于PC或服务器平台的人脸识别系统已无法满足人们对便携性和易用性的需求。局限于人脸识别系统对计算能力与存储容量的要求,以及图像采集时的周围复杂条件,人脸识别在移动平台中的应用一直难以发展。但随着最近微电子技术与移动操作系统的飞速发展,人脸识别在移动平台中的应用也有了飞快的发展。本文则针对移动终端的特殊应用环境,对人脸识别系统进行了研究。 本文首先对移动环境下的人脸检测进行了研究,提出了一种基于YCgCr肤色模型后期校验的人脸检测算法。首先利用AdaBoost训练算法构建的人脸检测分类器完成人脸区域的初始定位;然后采用基于YCgCr色彩空间的肤色模型对初始检测结果进行校验,踢除误检出的类人脸区域。实验结果表明,该方法具有较高的检测率,能够解决复杂背景中的类人脸与类肤色问题。 其次,为确保图像中人脸大小、位置以及图像质量的一致性,本文提出一种针对移动环境的图像归一化处理方法。首先基于人脸检测完成人眼的检测以及双眼位置的精确定位;然后利用双眼坐标完成人脸图像的旋转、裁剪和缩放操作等几何归一化,获取到标准人脸图像;最后通过GIC校正与直方图均衡化完成图像的光照归一化。 然后,为适用移动平台,提出了一种改进的基于LBP的特征提取算法。该算法基于图像分块的思想,首先对原始图像提取特征直方图,然后对分块图像分别提取特征直方图联结在一起,最后按照一定的顺序组合所有特征直方图,以表征人脸。 最后,综合以上的研究,最终实现了一个基于Android平台的移动环境下的人脸识别系统。
英文摘要: With the widespread application of Internet, information security issues more and more attention by the public. Traditional face recognition system based on PC or Server platform has been unable to meet the demand for portability and ease of use. Confined to limited computing power, storage capacity and the complex conditions of image acquisition, the application of face recognition in mobile platform has been difficult to develop. With the development of micro-electronics technology and Mobile OS, provides a basis for face recognition system applications in mobile platforms. This paper is directed to the specific environment of mobile terminal and studied the face recognition system. First, study the face detection in mobile environments, proposed face detection algorithm based on YCgCr skin color model in Post-test. First, the face detection classifier constructed by AdaBoost algorithm to complete the initial positioning of the face region; And then using skin color model based on YCgCr color space check the initial results, kicked out the mistakenly face region. The experimental results show that this method has a high detection rate, and solve the mistakenly detected problems in complex background. Second, to ensure the face size, face location and image quality. This paper proposed an image processing method for iamge normalization. First, complete the eye detection based on face detection and precise positioning of the eyes position; Then using the coordinates of eyes completion geometric normalization includes rotation, cropping, and zoom-in of face image, access to the standard face image; Finally, completion illumination normalization includes GIC correction and histogram equalization. Third, for mobile platforms, proposed an improved feature extraction algorithm based on LBP. The algorithm based on the idea of image block. First, extract the features of the original image histogram, then linked together all image block histogram by a certain sequence, access to an end histogram to characterize the face. Finally, implement a face recognition system based on the Android platform in mobile environment.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9419
Appears in Collections:信息服务与智能控制技术研究室_学位论文

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Recommended Citation:
鄂生强.移动环境下的人脸识别系统研究.[硕士学位论文].中国科学院沈阳自动化研究所.2012
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