Adaptive Moving Cast Shadow Detection by Integrating Multiple Cues

Moving cast shadow detection and removal is a key step for accurate object detection in intelligent transportation system. This paper proposes a robust cast shadow detection algorithm by integrating multiple cues. Firstly, a weak shadow detector is adopted to detect these potential shadow pixels; Then three adaptive shadow es- timators are designed and cascaded to integrate texture, chromaticity, brightness as well as spatial-temporal context for eliminating the object pixels so that this algorithm can robustly detect the moving cast shadow in the various envi- ronments; Lastly, spatial adjustment is employed to verify the shadow detection results of these three shadow esti- mators. Experimental results on indoor and outdoor video sequences show that this proposed algorithm can robustly detect moving cast shadow and rapidly adapt to variations in traffic surveillance scenarios.     

Multi-source Local Color Transfer Based on Texture Similarity

In order to realize automatic region matching between source and target images, a multi-source local color transfer algorithm based on texture similarity is proposed. The source and target images are segmented into a set of regions using an image segmentation algorithm. It computes the texture features of each region through the gray level co-occurrence matrix and then constructs corresponding texture feature vectors. The authors measure the relevance between the target and source regions by computing the Euclidean distance between corresponding tex- ture feature vectors. The source region having the largest relevance with the target region is selected as the transfer source. Complete the color transfer by performing color space transformation and linear conversion on color values. Experimental results concerning on multi-source local color transfer and gray image colorization verify the validity of the proposed algorithm.     

Construction and Count of 1-Resilient Rotation Symmetric Boolean Functions on pr Variables

Construction and count of 1-resilient Rotation symmetric Boolean functions （RSBFs） on pr variables are demonstrated. It is proved that constructions of 1-resilient RSBFs on pr variables are equivalent to solving an equation system. An accurate enumeration formula of all 1-resilient RSBFs on pr variables is also proposed. Some examples are given, and the exact numbers of 1-resilient RSBFs on 8 and 9 variables are obtained respectively.     

多尺度Gabor小波变换在图像检索中的应用

在基于内容的图像检索中,纹理特征是一种重要而又难以描述的特征。为提高图像检索中纹理特征的提取效率,通过对Gabor滤波器滤波特点的研究,提出一种基于多尺度Gabor小波纹理的图像检索方法。设计了一组具有多种尺度和多个方向的滤波器组,选择并优化滤波器组的各参数,对图像进行滤波和特征提取。设计并实现了一个基于Gabor纹理...     

基于Gabor小波变换的人脸表情识别

在人脸表情识别中,针对Gabor小波变换特征维数很大的问题,提出了一种新的多方向特征编码方法。通过对Gabor特征幅值进行统计处理,将每个像素点同一尺度不同方向的Gabor特征幅值闽值化成二进制,加强了Gabor小波对图像局部结构信息的表征。同时,结合了类似旋转不变LBP的方法对图像进行降维。为了进一步提高表情的正确识别率,采用一种局部区域融合的方法,最后在JAFFE表情库上进行测试,得到比较好的识别率,验证了所提方法的有效性。     

基于Gabor滤波器医学图像的纹理分割

基于Gabor滤波器纹理分割的研究。Gabor滤波器的改进,对Gabor滤波器在方向上做了改进,把Gabor滤波器在4个方向上提取纹理特征,拓展成在6个方向上提取纹理特征,基本满足了多通道多分辨率的要求。     

Fast feature extraction method for robust face verification

A feature extraction technique for face verification is proposed. It utilises polynomial coefficients derived from 2D discrete cosine transform (DCT) coefficients of neighbouring blocks. Experimental results suggest that the technique is more robust against illumination direction changes than 2D Gabor wavelets, 2D DCT and eigenface methods. Moreover, compared to Gabor wavelets, the proposed technique is over 80 times quicker to compute.     

Construction of Hilbert Transform Pairs of Wavelet Bases and Gabor-Like Transforms

We propose a novel method for constructing Hilbert transform (HT) pairs of wavelet bases based on a fundamental approximation-theoretic characterization of scaling functions—the B-spline factorization theorem. In particular, starting from well-localized scaling functions, we construct HT pairs of biorthogonal wavelet bases of ${rm L}^2({BBR})$ by relating the corresponding wavelet filters via a discrete form of the continuous HT filter. As a concrete application of this methodology, we identify HT pairs of spline wavelets of a specific flavor, which are then combined to realize a family of complex wavelets that resemble the optimally-localized Gabor function for sufficiently large orders. Analytic wavelets, derived from the complexification of HT wavelet pairs, exhibit a one-sided spectrum. Based on the tensor-product of such analytic wavelets, and, in effect, by appropriately combining four separable biorthogonal wavelet bases of ${rm L}^2({BBR}^2)$, we then discuss a methodology for constructing 2-D directional-selective complex wavelets. In particular, analogous to the HT correspondence between the components of the 1-D counterpart, we relate the real and imaginary components of these complex wavelets using a multidimensional extension of the HT—the directional HT. Next, we construct a family of complex spline wavelets that resemble the directional Gabor functions proposed by Daugman. Finally, we present an efficient fast Fourier transform (FFT)-based filterbank algorithm for implementing the associated complex wavelet transform.      

多母小波自适应小波滤波器

利用自适应小波变换（AWT）能融合不同母小波的优点,采用盖伯母小波和墨西哥帽母小波构成自适应小波.以光学人脸识别中降噪问题为应用背景,使用神经网络法对小波参数和组合系数进行优化,将生成的多母小波自适应小波滤波器用作人脸特征提取器.对噪声图像做特征提取,进行相关识别,采用3个指标定量分析识别结果.同盖伯小波和墨西哥帽小波识别结果的比较表明,多母小波自适应小波具有不同母小波的优点,并有良好的降噪性能.     

基于Gabor小波的无边缘活动围道纹理分割方法

该文提出了一种基于Gabor小波的活动围道纹理分割新方法。该方法先用Gabor小波提取图像的纹理特征,再用Chan-Vese模型进行分割。与其它基于Chan-Vese模型的纹理分割方法相比,基于Gabor小波的活动围道的纹理分割方法有两个优点:一是同时使用纹理特征和灰度信息演化围道,可分割纹理图像和非纹理图像,分割方法的灵活性好;二是在分割多类目标时,采用多级分层式曲线演化方法解决了初始围道难以选择的问题。对自然界真实图像和遥感图像的分割实验结果说明,该文提出的分割方法精度高。     

Model Space Results for the Gabor and Wavelet Transforms

We prove that the unique Gabor window leading to an analytic model space is the Gaussian one, and we give an analogous result for the wavelet transform. For the general case we give a new approach to study irregular Gabor and wavelet frames. We improve some known results for Gabor windows in the Feichtinger algebra, and for a special class of wavelets.     

基于二维Gabor小波的人脸识别算法

该文提出了一种基于二维Gabor小波的人脸识别算法。该算法先对人脸图像进行多分辨率的Gabor小波变换,然后在图像上放置一组网格结点,每个结点用该结点处的多尺度Gabor幅度特征描述,采用主元分析法对每个结点进行去相关、降维,最后形成特征结。把每个特征结作为观测向量,对隐马尔可夫模型进行训练,并把优化的模型参数用于人脸识别。实验结果表明,该方法识别率高,复杂度较低。     

基于Gabor环滤波的纹理分割方法

针对纹理分割问题,提出了一种在频率域呈环形分布的Gabor滤波器组(Gabor环)的设计方法,在能量意义下给出了自适应选择滤波环带的步骤,并给出了经Gabor滤波后纹理特征的计算公式。根据给定Gabor滤波器环具有的多方向特性对不同纹理图像进行滤波,然后计算滤波后各点特征,并利用这些多方向特征进行纹理分割。实验表明该方法能取得较好的分割效果,并具有很强的通用性。     

二维滑动矩形窗傅氏变换的快速递推算法

该文利用相邻滑动窗数据之间的关系以及傅氏变换的平移性质,提出一种二维滑动矩形窗傅氏变换的快速递推算法。文中分析了该快速递推算法的复杂度和传统直接计算法的复杂度,证明了新的快速递推法可以大大降低计算复杂性,尤其是在图像尺寸和窗口尺寸较大的场合中。该算法可以改善滑窗傅氏变换或Gabor变换的计算效率。     

Shannon小波包分解自适应Gabor滤波器设计及其在纹理分割中的应用

本文首先研究了Ｇａｂｏｒ滤波器进行确定性纹理分割时纹理结构与Ｇａｂｏｒ函数的关系，提出了利用在频域中具有紧支集的Ｓｈａｎｎｏｎ小波包分解检测纹理的主频；最后，提出了基于小波包分解自适应Ｇａｂｏｒ函数与纹理图像卷积，就可以在纹理的连续处产生良好的阶跃边缘，并通过实验验证了该算法的有效性及其对噪声的鲁棒性。     

利用Gabor小波系数融合进行图像增强的研究

在传统图像增强技术的基础上,提出了一种基于GABOR小波系数融合的图像增强方法。通过Gabor小波对图像进行滤波,产生八个方向的滤波图像系数,对这些图像系数用求平均值融合方法得到图像边缘图,再融合经传统空域增强方法得到的直方图均衡化图像以产生最终增强的边缘信息以便于分析处理的图像。     

Gabor-based kernel PCA with doubly nonlinear mapping for face recognition with a single face image.

In this paper, a novel Gabor-based kernel principal component analysis (PCA) with doubly nonlinear mapping is proposed for human face recognition. In our approach, the Gabor wavelets are used to extract facial features, then a doubly nonlinear mapping kernel PCA (DKPCA) is proposed to perform feature transformation and face recognition. The conventional kernel PCA nonlinearly maps an input image into a high-dimensional feature space in order to make the mapped features linearly separable. However, this method does not consider the structural characteristics of the face images, and it is difficult to determine which nonlinear mapping is more effective for face recognition. In this paper, a new method of nonlinear mapping, which is performed in the original feature space, is defined. The proposed nonlinear mapping not only considers the statistical property of the input features, but also adopts an eigenmask to emphasize those important facial feature points. Therefore, after this mapping, the transformed features have a higher discriminating power, and the relative importance of the features adapts to the spatial importance of the face images. This new nonlinear mapping is combined with the conventional kernel PCA to be called "doubly" nonlinear mapping kernel PCA. The proposed algorithm is evaluated based on the Yale database, the AR database, the ORL database and the YaleB database by using different face recognition methods such as PCA, Gabor wavelets plus PCA, and Gabor wavelets plus kernel PCA with fractional power polynomial models. Experiments show that consistent and promising results are obtained.     

A tutorial on wavelets from an electrical engineering perspective.2. The continuous case

The wavelet transform is described from the perspective of a Fourier transform. The relationships among the Fourier transform, the Gabor (1946) transform (windowed Fourier transform), and the wavelet transform are described. The differences are also outlined, to bring out the characteristics of the wavelet transform. The limitations of the wavelets in localizing responses in various domains are also delineated. Finally, an adaptive window is presented that may be optimally tailored to suit one's needs, and hence, possibly, the scaling functions and the wavelets     

光学子波变换（3）：应用

本文综述了子波变换的发展概况，总结了光学子波变换的一些应用领域，重点论述了在纹理分割中的应用，提出了联合子波变换相关器及其应用于二值图象的特征提取，给出了多通道盖伯变换在纹分割中的应用设想以及初步的研究结果。     

基于Gabor小波的人脸表情特征提取研究

为了使计算机能更好的识别人脸表情,对基于Gabor小波变换的人脸表情识别方法进行了研究。首先对包含表情区域的静态灰度图像进行预处理,包括对确定的人脸表情区域进行尺寸和灰度归一化,然后利用二维Gabor小波变换提取脸部表情特征,使用快速PCA方法对提取的Gabor小波特征初步降维。再在低维的空间中,利用Fisher准则提取那些有利于分类的特征,最后用SVM分类器进行分类。实验结果表明,上述提出的方法比传统的方法识别速度更快,能达到实时性的要求,并且具有很好的鲁棒性,识别率高。