[基础科学]人脸检测论文:快速人脸检测与识别技术的研究.doc
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1、 人脸检测论文:快速人脸检测与识别技术的研究【中文摘要】随着信息技术高速发展,人脸检测与识别技术具有越来越广泛的应用价值和重要的理论研究价值,已成为图像处理、人工智能、模式识别等领域中研究最为热点的课题之一。在研究国内外相关文献及最新研究成果的基础上,本文对人脸检测与识别技术进行系统性理论研究,主要包括两方面的内容:基于肤色信息的快速人脸检测算法和基于线性子空间分析的人脸识别算法及其相应的改进算法:1.在人脸检测方面,本文主要利用肤色信息对彩色图像进行快速人脸检测。首先,对彩色图像进行必要预处理,采用自适应光线补偿算法;然后,用标准化rgb颜色空间的多项式模型对光线补偿后的彩色图像进行肤色区域
2、粗检测;接着,将标准化rgb颜色空间的多项式模型和经过非线性修正后的YC_g C_r颜色空间的高斯模型相结合构成混合肤色模型,对粗检测肤色区域做进一步精确肤色区域提取;最后,分析二值图像的连通区域,用椭圆面积准则验证人脸候选区域是否有人脸。2.在人脸识别方面,对传统主成分分析和线性判别分析进行研究,主要对二维主成分分析和二维线性判别分析的人脸识别算法进行研究并提出相应的改进算法并进行仿真。本文提出在图像矩阵的行和列两个方向上同时进行特征提取的改进算法,即有基于加权(2D)2 -PCA人脸识别算法和(2D)2-LDA人脸识别算法,这两种算法能够消除图像行、列各自的相关性,减少特征数量,减小存储空
3、间,提高识别速率。3.在人脸识别中,由于用于识别的人脸样本数一般远远小于人脸样本的维数,经常出现小样本问题。所以,本文提出了一种采用Gabor小波变换的人脸识别算法来解决人脸识别中小样本问题,即把人脸样本图像经过Gabor小波变换后得到的每幅图像都看成独立人脸样本,这样就可以在保持每类原样本数不变的情况下大大地增加了每类人脸的样本数,并和改进的LDA人脸识别算法相结合,构成Gabor+(2D)2-LDA人脸识别算法。当每类训练样本数很少时,该算法能有效地提高人脸识别率,且识别性能比较稳定。【英文摘要】With the rapid development of information techn
4、ology, the technology of face detection and recognition is provided with extensive application value and theoretical value, which has become one of hot topic in the fields of image processing, artificial intelligence, pattern recognition and so on. Based on the study of related literature and the la
5、test research results, technology theory of face detection and recognition is systematically studied in the thesis, which mainly includes two aspects of content: the skin color information based fast face detection algorithm and the linear space analysis based face recognition algorithm and its impr
6、oved algorithm:1. About the aspects of the face detection, color information is used for rapid face detection. Firstly, an adaptive light compensation algorithm is used for the color image preprocessing; secondly, the polynomial model of standardized rgb color space is used for the rough detection o
7、f skin color area in the color images through light compensation; then, mixed skin model which is combined the polynomial model of standardized rgb color space with the gaussian model of the nonlinear transform color space of the YCgCris used for more accurate color regional extraction in the skin a
8、rea of rough detection;finally, binary image the connected area is analyzed and elliptic area criterion is used to verify whether the face candidate area have face.2. About the aspects of the face recognition, the thesis studies the traditional principal component analysis and linear discriminative
9、analysis, and mainly studies the face recognition algorithm of two-dimensional principal component analysis and two-dimensional linear discriminant analysis, then puts forward the improved algorithm and simulation. This thesis proposes a improved feature extraction algorithm which is simultaneously
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