| 基于离散余弦变换基函数迭代的人脸图像识别 |
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| 作者姓名： | 于万波 王香香 王大庆 |
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| 作者单位： | 大连大学信息工程学院，辽宁大连 116622 |
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| 摘 要： | 使用非线性混沌方法处理与识别图像的研究工作逐渐增多，已有文献给出了一种
将正弦函数作为辅助函数与图像构造动力系统，迭代生成混沌吸引子作为图像特征。为进一步
探究图像吸引子作为图像的特性，改进识别效果，使用离散余弦变换(DCT)基函数矩阵代替正
弦函数，迭代生成近似混沌吸引子，用于人脸识别。首先，研究分析了DCT 基函数矩阵的多样
性与振荡特性；然后利用DCT 基函数矩阵与图像矩阵构造迭代表达式，通过给出的迭代算法使
其产生吸引子，再对吸引子进行快速傅里叶变换，计算相关系数，识别人脸图像。对于Yalefaces
图像库，每幅图像都参加训练，识别率可以达到100%，当使用每组前5 幅图像训练提取特征，
识别率可以超过85%；对于CMU PIE 数据库，每幅图像都参加训练，识别率可以超过99%。
该吸引子方法可以作为一种图像底层特征提取方法，有待于进一步深入研究。
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| 关 键 词： | 人脸识别 动力系统 混沌吸引子 图像特征 |
Face image recognition based on basis function iteration of discrete cosine transform |
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| Authors: | YU Wan-bo WANG Xiang-xiang WANG Da-qing |
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| Affiliation: | College of Information, Dalian University, Dalian Liaoning 116622, China |
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| Abstract: | The research work of image processing and recognition by means of non-linear chaotic method is receiving increasing attention.In the existing literature,there has been a method which constructs dynamic system by taking sinusoidal function as auxiliary function and image,and iteratively generates chaotic attractors as image features.In order to further explore the characteristics of image attractors as image features and improve the recognition effect,this paper uses a discrete cosine transform(DCT)basis function matrix instead of a sine function to generate approximate chaotic attractors iteratively for face recognition.First,this study analyzes the diversity and oscillation of DCT basis function matrix.Then,the DCT basis function matrix and the image matrix are used to construct the iterative expression,and the proposed iterative algorithm is used to generate the attractor.After the attractor is transformed by fast Fourier transform,the correlation coefficient is calculated,and the face image is recognized.For the Yalefaces image database,when each image can be trained,the recognition rate can reach 100%.When the first five images of each group are trained to extract the feature,the recognition rate can exceed 85%.For CMU PIE databases,when each image can be trained,the recognition rate can exceed 99%.And this attractor method can be used as a method of image bottom feature extraction,which still needs further study. |
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| Keywords: | face recognition discrete cosine transform basis function chaotic attractor image features |
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