基于小波变换和kd树聚类的快速纹理分割算法

提出了一种基于小波变换和k均值聚类的快速纹理图像分割算法。该方法包括特征提取、特征平滑、纹理分割三个阶段。其中,特征提取在金字塔结构小波变换的基础上进行;特征平滑利用一种四分法来完成特征图像的噪声平滑和边缘保持;纹理分割则利用kd树作为数据结构来运行k均值聚类算法从而实现纹理图像的快速分割。实验结果表明与直接的k均值聚类算法相比,该方法在运行时间上得到了明显的提高。     

基于小波变换和纹理特征的水印算法的研究

目前基于小波变换的数字水印算法主要根据频域小波系数的幅值大小确定是否嵌入水印,这种算法的缺点是嵌入水印后的图像的视觉透明度不够好。对目前已有的基于小波变换的数字水印算法进行了研究,在保证嵌入水印的鲁棒性的前提下,也保证嵌入水印后的图像的理想的视觉效果的基础上,提出了一种基于小波变换和图像纹理特征的自适应数字水印算法,该算法利用了图像本身固有的纹理特征来寻找水印的嵌入位置,实验结果表明该方法能较好地降低原始图像视觉失真和经压缩变换后水印图像的失真。     

基于Contourlet变换的纹理特征提取及纹理分类

通过对传统小波多方向性缺失和Contourlet变换系数稀疏性的分析,提出运用方向性小波Contourlet分析纹理特征,以自组特征映射神经网络(SOM)处理Contourlet变换系数的重组序列.对SOM网络输出层codebook矩阵进行奇异值分解得到纹理图像特征向量的方法进行纹理分类,在充分利用图像各尺度方向信息的基础上,有效提取了图像纹理特征.实验结果表明,该方法分类效果显著,Contourlet变换比传统小波分解更适合于图像纹理特性的分析.     

A new approach to feature selection based on the Karhunen-Loeve expansion

After surveying existing feature selection procedures based upon the Karhunen-Loeve (K-L) expansion, the paper describes a new K-L technique that overcomes some of the limitations of the earlier procedures. The new method takes into account information on both the class variances and means, but lays particular emphasis on the classification potential of the latter. The results of a series of experiments concerned with the classification of real vector-electrocardiogram and artificially generated data demonstrate the advantages of the new method. They suggest that it is particularly useful for pattern recognition when combined with classification procedures based upon discriminant functions obtained by recursive least squares analysis.     

An effective method for color image retrieval based on texture

This paper presents an effective color image retrieval method based on texture, which uses the color co-occurrence matrix to extract the texture feature and measure the similarity of two color images. Due to the color information such as components and distribution is also taken into consideration, the feature obtained not only reflects the texture correlation but also represents the color information. As a result, our proposed method is superior to the gray-level co-occurrence matrix method and color histogram method, and it enhances the retrieval accuracy which is measured in terms of the recall and precision in the meanwhile.     

Off-line signature verification based on grey level information using texture features

A method for conducting off-line handwritten signature verification is described. It works at the global image level and measures the grey level variations in the image using statistical texture features. The co-occurrence matrix and local binary pattern are analysed and used as features. This method begins with a proposed background removal. A histogram is also processed to reduce the influence of different writing ink pens used by signers. Genuine samples and random forgeries have been used to train an SVM model and random and skilled forgeries have been used for testing it. Results are reasonable according to the state-of-the-art and approaches that use the same two databases: MCYT-75 and GPDS-100 Corpuses. The combination of the proposed features and those proposed by other authors, based on geometric information, also promises improvements in performance.     

An effective algorithm for fingerprint image enhancement based on wavelet transform

Among all the fingerprint identification/verification systems, such as minutiae-based or filterbank-based fingerprint matching, the performance relies heavily on the quality of the input fingerprint images. In this paper, we propose an effective algorithm of fingerprint image enhancement, which can much improve the clarity and continuity of ridge structures based on the multiresolution analysis of global texture and local orientation by the wavelet transform. Experimental results show that the enhanced image quality by using the wavelet-based enhancement algorithm is much better than the other existing methods for improving the minutiae detection.     

基于OSG的规则多面体重构和纹理映射技术

对物体进行纹理贴图的主要方法是将纹理坐标同物体表面顶点坐标建立关联,但是在建模软件之外由于没有物体的顶点坐标信息,要实现纹理映射相当困难.在OSG的基础上,采用重构规则物体表面的方法实现了物体的按面纹理映射,并得到了预期的效果.     

基于提升小波变换的图像融合新算法

给出了一种基于提升小波变换的图像融合方法,并对小波分解的不同频率域,分别采用不同的融合规则。选择低频系数时,是基于边缘的方法,选择高频系数时,把小波系数的方差与绝对值综合起来考虑来决定融合小波系数。实验结果表明,提出的方法融合效果要优于一般融合方法。     

基于局部累积直方图和纹理特征的图像检索方法

提出了结合HSI颜色空间的局部累积直方图和图像的纹理特征进行检索的新方法.在HSI颜色空间求局部累积直方图,既可以消除大量离散的零值点,又考虑到累积前后两种颜色的相似性,符合人眼的视觉感知特点;利用以灰度共生矩阵为基础的纹理特征对局部累积直方图检索的结果进行二次检索,充分考虑了图像的空间信息.避免单一的颜色特征描述图像的片面性.基于花卉图像库的检索实验结果表明,该方法可以取得良好的检索效果.     

Combining spatial and colour information for content based image retrieval

Colour is one of the most important features in content based image retrieval. However, colour is rarely used as a feature that codes local spatial information, except for colour texture. This paper presents an approach to represent spatial colour distributions using local principal component analysis (PCA). The representation is based on image windows which are selected by two complementary data driven attentive mechanisms: a symmetry based saliency map and an edge and corner detector. The eigenvectors obtained from local PCA of the selected windows form colour patterns that capture both low and high spatial frequencies, so they are well suited for shape as well as texture representation. Projections of the windows selected from the image database to the local PCs serve as a compact representation for the search database. Queries are formulated by specifying windows within query images. System feedback makes both the search process and the results comprehensible for the user.     

小波变换的稀疏最优化信号趋势项提取方法

针对非线性信号的趋势项,提出一种基于小波变换的稀疏最优化方法(WT-SO).该方法通过设置两个边界约束条件,求取l1范数稀疏最优解重构信号趋势项.仿真信号与实测信号处理结果表明:该方法依据信号自身的特性来定义趋势项,不需要对信号作任何假设,比传统的提取趋势项的方法具有更高的精度和可靠性,且在各种噪声环境下均具有良好的鲁棒性.     

基于纹理和高斯密度特征的图像检索算法

直接从DCT域中提取图像的特征是提高图像的检索效率的方法.直接从压缩域中提取图像的高斯密度,即计算图像在8个方向上的分段累加值,形成一个8*4的二维向量,再结合图像的纹理特征来进行图像检索.为了验证算法的可行性,建立了10000幅图像的图像库.实验结果表明,该方法能够准确地检索出目标图像,有效地提高了图像检索的精度和速度.     

基于双树复小波和灰度共生矩阵的遥感图像分割

提出了一种将双树复小波变换和灰度共生矩阵相结合描述遥感图像局部纹理特征并用于分割的方法。该方法采用双树复小波高频模值子带Gamma分布与Lognormal分布参数组合特征、灰度共生矩阵特征组成的联合纹理特征作为遥感图像每一像素特征,然后用Canberra距离进行相似性度量,最终通过聚类完成遥感图像分割。实验结果表明,该纹理特征提取方法可以有效地表征遥感图像的纹理,得到更为精确的遥感图像分割结果。     

Convolution theorems for the linear canonical transform and their applications

As generalization of the fractional Fourier transform (FRFT), the linear canonical transform (LCT) has been used in several areas, including optics and signal processing. Many properties for this transform are already known, but the convolution theorems, similar to the version of the Fourier transform, are still to be determined. In this paper, the authors derive the convolution theorems for the LCT, and explore the sampling theorem and multiplicative filter for the band limited signal in the linear canonical domain. Finally, the sampling and reconstruction formulas are deduced, together with the construction methodology for the above mentioned multiplicative filter in the time domain based on fast Fourier transform (FFT), which has much lower computational load than the construction method in the linear canonical domain.     

Discrete fractional Fourier transform based on the eigenvectors of tridiagonal and nearly tridiagonal matrices

The recent emergence of the discrete fractional Fourier transform (DFRFT) has caused a revived interest in the eigenanalysis of the discrete Fourier transform (DFT) matrix F with the objective of generating orthonormal Hermite–Gaussian-like eigenvectors. The Grünbaum tridiagonal matrix T—which commutes with matrix F—has only one repeated eigenvalue with multiplicity two and simple remaining eigenvalues. A detailed eigendecomposition of matrix T is performed with the objective of deriving two orthonormal eigenvectors—common to both the F and T matrices—pertaining to the repeated eigenvalue of T. The nearly tridiagonal matrix S first introduced by Dickinson and Steiglitz and later studied by Candan et al.—which commutes with matrix F—is rigorously proved to reduce to a 2×2 block diagonal form by means of a similarity transformation defined in terms of an involutary matrix P. Moreover explicit expressions are derived for the elements of the two tridiagonal submatrices forming the two diagonal blocks in order to circumvent the need for performing two matrix multiplications. Although matrix T has the merit of being tridiagonal and does not need the tridiagonalization step as matrix S, the simulation results show that the eigenvectors of matrix S better approximate samples of the Hermite–Gaussian functions than those of matrix T and moreover they have a shorter computation time due to the block diagonalization result. Consequently they can serve as a better basis for developing the DFRFT.     

A method for detection of circular arcs based on the Hough transform

The circular arc is a very useful feature for object detection and recognition in industrial environments. In this paper, a method for detection of circular arcs is described that is based on the Hough transform. The method estimates all five arc parameters and is robust in the presence of a moderate amount of noise. It has a computational and memory complexity ofO(n·m·R) andO(n·m) respectively, wheren andm are the sizes in thex andy directions andR is the maximum expected arc radius in pixels. Arcs as small as 45 degrees and radii down to 4 pixels can be detected. The computing time is almost independent of the number of circular arcs in the image.This work was supported by the Swedish Board for Technical Development, Grant No. 87-01954P.     

基于改进四元傅里叶变换的显著性检测及其视频编码应用

针对基于感兴趣区域的有损视频压缩在低码率编码条件下容易产生明显的编码人工痕迹,提出一种基于注意力权重矩阵的四元傅里叶变换的视觉显著性视频编码模型。该方法引入人眼视觉注意力权重矩阵对不同区域图像四元数予以加权,该四元数由图像的亮度、色度和运动特征组成。图像视觉显著图可由其四元数特征的四元傅里叶相位谱获取。结合中心凹恰可觉察失真(FJND)模型将其应用于基于感兴趣区域视频编码,可提高视频编码质量。与五种流行的显著性检测算法在两个大型眼动跟踪数据库上进行对比实验,结果表明提出的算法显著性检测精度明显高于对比算法。此外,与最新的基于显著性视频编码方法在10段标准视频上进行编码视频的主观质量对比,该方法能提高低码率编码视频的主观视觉质量,且优于对比算法。     

MIMO-OFDM system based on fractional Fourier transform and selecting algorithm for optimal order

In the rapidly time-varying channel environment, the performance of traditional MIMO-OFDM system is deteriorated due to the intercarrier interference. In this paper, a novel MIMO-OFDM system is proposed, in which the modulation and de- modulation of the symbols are implemented by the fractional Fourier transform instead of traditional Fourier transform. Through selecting the optimal order of the fractional Fourier transform, the modulated signals can match the time-varying channel characteristics, which results in a mitigation of the intercarrier interference. Furthermore, an algorithm is presented for selecting the optimal order of fractional Fourier transform, and the impact of system parameters on the optimal order is analyzed. Simulation results show that the proposed system can concentrate the power of desired signal effectively and improve the performance over rapidly time-varying channels with respect to the traditional MIMO-OFDM system.