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基于 Gabor 变换的特征分析及其应用
其他题名Gabor Transform Based Feature Analysis and Its Applications
朱振峰
学位类型工学博士
导师卢汉清
2005
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词Gabor 变换 边缘检测 目标匹配 K-l 散度 目标检测 支持向量机 Gabor Transform Edge Detection Object Matching K-l Divergence
摘要时频分析是信号处理中的重要手段之一。Gabor 变换,又称短时或加窗Fourier 变换,克服了传统 Fourier 变换在频域内无任何时域分辨力的缺陷,体现了信号的联合时频分析特性。在 Heisenberg 测不准原理下,它被证明具有最优的联合时频分辨率。同时,通过对人的感知系统的生理学特性研究表明,二维 Gabor 基函数能够很好的描述哺乳动物初级视觉系统中大多数简单视觉神经元的感受野特性。本文的目的是通过对图像信号进行基于 Gabor 变换的时频分析,开展模式检测方面的相关技术研究。本文工作的贡献体现在: 1) 从时频分析角度出发,对 Gabor 变换的时频特性进行了分析。对其在纹理分割、图像检索、目标检测、目标识别等方面的典型应用展开了论述。 2) 在边缘检测方面,对基于奇 Gabor 滤波器的边缘响应输出进行了分析,提出了一个基于 Rayleigh 分布的非线性自适应阈值选择方法。在此基础上,通过对奇 Gabor 变换进行多尺度特性分析,提出了一个奇 Gabor 变换域内基于尺度积的边缘检测算法。实验表明,该算法同常用的边缘检测算子相比,具有更强的抗噪性能及更好的视觉检测效果。 3) 利用圆形 Gabor 变换的旋转不变性,提出了一个基于加权的部分 Hausdorff距离的鲁棒目标匹配方法。在加有位置信息的圆形 Gabor 特征空间,利用加权的部分 Hausdorff 距离实现了目标的粗匹配。此后,通过结合圆形 Gabor 特征与目标的形状信息,实现了目标的精匹配。实验表明所提出的算法对于噪声、遮挡、旋转及一定的尺度变化具有鲁棒性。4) 为解决上述匹配算法的效率问题,提出了一个基于假设、验证的两步目标匹配方法。首先把目标匹配过程分解为多个局部优化过程,借以减小目标匹配中的搜索路径;然后利用基于 K-L 散度的均值漂移技术实现局部优化,从而实现假设集(局部优化的收敛点)的快速产生。在局部寻优过程中,提出了一个系数修正方法,从而在理论上确保迭代寻优过程的收敛。
其他摘要Temporal-Frequency Analysis is one of most important tools for signal processing. Gabor Transform, which is also named by Short-Time Fourier Transform or Windowed Fourier Transform,shows the joint temporal -frequency property of signal analysis and overcomes the shortcomings of traditional Fourier Transform which fails to present any temporal discrimination ability in frequency domain. Under Heisenberg’s uncertainty principle, it has been proved that it has optimal joint temporal-frequency resolution. Based on the studies on the physiology of mammal perception system, it has been shown that 2-D Gabor Elementary Function can fit well the receptive fields of the majority of simple cells in mammal visual cortex. All works presented in the dissertation are to conduct pattern detection related researches by means of Gabor Transform based joint Temporal-Frequency Analysis. The main contribution of the dissertation are as follows: 1) From the view of Temporal-Frequency Analysis,the temporal-frequency property of Gabor Transform is analyzed. Some Gabor Transform based typical applications are discussed, which include texture segmentation, image retrieval, object detection, and object recognition. 2) In edge detection, the edge output response based on Odd Gabor Transform is analyzed and a nonlinear adaptive threshold selection scheme based on Rayleigh distribution is proposed. Following the above works, the multi-scale analysis in Odd Gabor Transform domain is conducted and scale multiplication in Odd Gabor Transform domain for edge detection is put forward. The final experimental results show the proposed algorithm has stronger noise resisted capability and better visual effect compared with other common utilized edge detection operators. 3) Based on the rotation invariant property of Circular Gabor Transform,a robust object matching method by using weighted partial Hausdorff distance is proposed. In circular Gabor feature space with position information embedded, a coarse object matching is realized by using weighted partial Hausdorff distance. Then the final fine object matching is obtained by combining the circular Gabor features and the object’s shape information. The experimental results show that the proposed algorithm is robust to the influences from the cases of noise, occlusion, rotation variation, and scale variation. 4) For the consideration of computing efficiency of the above mentioned object matching method, a two-step object matching scheme based on hypothesis generation and verification is proposed. First the procedure of object matching is decomposed into multiple local optimizations to shorten the search paths for object candidates. Then the mean shift based local optimization technique with K-L divergence as similarity measure is utilized to generate fast the hypothesis set. In the process of local optimizing, a coefficient adjustment method is given to ensure the theoretic convergency of iterative optimizing.
馆藏号XWLW892
其他标识符200118014604906
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/5832
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
朱振峰. 基于 Gabor 变换的特征分析及其应用[D]. 中国科学院自动化研究所. 中国科学院研究生院,2005.
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