图像维数计算方法及其实质研究

基于颜色单元体模型,本文提出了一种间接量测表面形貌的新方法——真彩图像维数计算方法,并通过激光表面仪扫描实验对此进行了验证。该计算方法的提出,使在表面形貌的实验研究中用拍摄数码照片方法取代激光表面仪扫描成为可能。比较研究显示,该方法具有简单、方便、直观和扫描范围大等优势,是表面形貌实验研究手段上的一大改进。本文还分别探讨了二值化图像,灰度图像,真彩图像的分形特性,剖析了三类图像维数的物理实质。比较研究结果显示,对于同一试样,真彩图像维数最大,灰度图像次之,二值化图像维数最小,其维数在区间[1,2]内。以此说明,二值化图像维数是曲线维数,灰度图像维数仅考虑了颜色明度值的影响,只有真彩图像维数充分考虑了色彩、色饱和度和明度值的"贡献",该维数才是"全局"意义上的图像维数。

免疫荧光图像中神经突起的分维研究

分形维数已经广泛应用于医学图像处理分析中。我们介绍一种基于三棱形表面积(Triangular prismsurface area,TPSA)的分形维数测定方法,并将它创造性地应用于免疫荧光图像中,定量分析不同浓度神经再生素对大鼠背根神经节神经突起生长的影响。实验表明:基于分维的神经突起生长状况的研究易于理解,便于操作,与显微镜观测结果一致,其定量结果对实验的分析和判断具有很好的指导作用。

多小波图像去噪算法的研究

尽管多小波相比于单小波,具有正交性、紧支撑、实对称、高阶消失矩等性质,但是多小波进行图像去噪效果并不是很理想,其主要原因是没有充分利用图像在多小波域内所特有的性质.通过将含噪图像变换到多小波域,在小波域内应用Laplace算子的一种特殊差分格式,并考虑小波域内各个子带的分形维数,提出了一种自适应的多小波阈值算法,即AMT算法.对于欲去噪的图像,AMT算法能够在多小波域内自动确定去噪的小波伸缩阈值,而不需要知道图像的任何先验知识,例如图像中噪声的方差等等.仿真实验结果表明,该算法去噪效果好,特别是对于高度污染的图像,AMT算法的去噪效果更加显著.

多小波图像插值算法研究

与单小波变换一样,多小波变换同样具有多分辨分析的特性,1次多小波变换可以将图像分解成4个低频子带和12个高频子带,而且原图像的大小是每个子带的4倍.根据多小波变换的这一特点,利用原图像与经过1次多小波变换后的各高频子带的信息,并考虑各子带的分形维数,提出了一种新颖的灰度图像插值算法.实验结果表明,与传统的插值算法相比,例如双线性插值与双三次多项式插值,该算法的插值效果较好,且克服了单小波插值中出现的斑点干扰.

一种基于多小波变换的自适应图像去噪算法

介绍一种新颖的自适应图像去噪算法。通过将图像变换到多小波域,并利用分形几何和图像的偏微分方程知识,提出一种新的图像软阈值去噪算法。对于欲去噪的图像,该算法能够在多小波域中,自动确定去噪阈值。实验结果表明,该算法不仅去噪效果好,而且运行稳定。

Experimental Study on Full-Surface Buckling of Variable Curvature Cylindrical Shell Using Multi-camera 3D-DIC System

To achieve full-surface strain measurement of variable curvature objects,a 360°3D digital image correlation(DIC)system is proposed.The measurement system consists of four double-camera systems,which capture the object’s entire surface from multiple angles,enabling comprehensive full-surface measurement.To increase the stitching quality,a hierarchical coordinate matching method is proposed.Initially,a 3D rigid body calibration auxiliary block is employed to track motion trajectory,which enables preliminary matching of four 3D-DIC sub-systems.Subsequently,secondary precise matching is performed based on feature points on the test specimen’s surface.Through the hierarchical coordinate matching method,the local 3D coordinate systems of each double-camera system are unified into a global coordinate system,achieving 3D surface reconstruction of the variable curvature cylindrical shell,and error analysis is conducted on the results.Furthermore,axial compression buckling experiment is conducted to measure the displacement and strain fields on the cylindrical shell’s surface.The experimental results are compared with the finite element analysis,validating the accuracy and effectiveness of the proposed multi-camera 3D-DIC measuring system.

基于分形损失理论的粗糙节理岩体中应力波波速研究

从损伤力学的基本理论出发,推导了应力波在节理岩石中传播波速的解析解,建立了节理面图像分形维数与波速间的关系。为了从数值角度探讨节理面图像维数对波速的影响规律,基于图像每一像素颜色可表示为一个三维空间矢量的基本假定,构建了节理面图像的粗糙"颜色表面"模型,计算了该"颜色表面"的分形维数,此维数即为节理面图像维数,并通过实例验证了该法的可行性。在此基础上,通过数值方法探讨了波速随图像维数的变化规律,研究显示:随着节理面图像维数增大,节理面粗糙程度的增加,应力波波速相应减小,且在不同的图像维数区间里,波速减小的速率也有所不同。

Fractal analysis of thermal conduction of loose coal

For deep mining engineering, heat transfer of coal mass is a vital factor in the thermal environment of coal mines. In order to study the thermal conduction mechanism, we obtained gray images of coal mass microstructure by scanning samples with a digital microscope. With the use of Matlab, these gray images were transformed into binary images, which were then transformed into a corresponding matrix consisting only of the values 0 and 1. According to the calculation method of box-counting dimension, we calculated the fractal dimension of the loose coal to be approximately 1.86. The thermal conductivity expressions of loose coal were derived based on the simulation method of thermal resistance. We calculated the thermal conductivity of loose coal by using a fractal model and compared the calculated values with our experimental data. The results show that the test data show an encourag-ing agreement with the calculated values. Hence fractal theory is a feasible method for studying thermal conductivity of loose coal.

An image retrieval system based on fractal dimension

This paper presents a new kind of image retrieval system which obtains the feature vectors of images by estimating their fractal dimension; and at the same time establishes a tree structure image database. After preprocessing and feature extracting, a given image is matched with the standard images in the image database using a hierarchical method of image indexing.

Pest Detection Method Using Multi-Fractal Analysis

A novel method for pest detection is proposed based on the theory of multi-fractal spectrum to extract pests on plant leaves.Both local and global information of the image regularity were obtained by multi-fractal analysis.By applying fractal dimension,the spots on leaf images can be extracted without loosing or introducing any information.The different parts of images are re-analysis by morphology operations to determine the candidate regions of pests.The performance of multi-fractal analysis of whitefly detection is investigated through greenhouse experiments.The experimental results show that the proposed method is robust to noise from light and is not sensitive to the complex environment.

3D Motion Parameters Determination Based on Binocular Sequence Images

Exactly capturing three dimensional (3D) motion i nf ormation of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision s ystem and a method for determining 3D motion parameters of an object from binocu lar sequence images are introduced. The main steps include camera calibration, t he matching of motion and stereo images, 3D feature point correspondences and re solving the motion parameters. Finally, the experimental results of acquiring th e motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned meth od are presented.

Texture image classification using multi fractal dimension

This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet decomposition are combined and a feature set based on multi-fractal dimension is obtained. In the part of classifier construction, the Learning Vector Quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification were carried out with satisfactory results, which verify the effectiveness of this method.

Visualization of Three-dimensional Human Data Based on CT Image

Three-dimensional medical image visualization becomes an essential part for medical field, including computer aided diagnosis, surgery planning and simulation, artificial limb surgery, radiotherapy planning, and teaching etc. In this paper, marching cubes algorithm is adopted to reconstruct the 3-D images for the CT image sequence in DICOM format under theVC＋＋6.0 and the visual package VTK platform. The relatively simple interactive operations such as rotation and transfer can be realized on the platform. Moreover, the normal vector and interior point are calculated to form the virtual clipping plane, which is then used to incise the 3-D object. Information of the virtual slice can be obtained, in the mean while the virtual slice images are displayed on the screen. The technique can realize the real time interaction extraction of virtual slice on 3-D CT image. The cuboids structured can be zoomed, moved and eircumrotated by operating mouse to incise the 3-D reconstruction object. Real time interaction can be realized by clipping the reconstruction object. The coordinates can be acquired by the mouse clicking in the 3D space, to realize the point mouse pick-up as well angle and distance interactive measurement. We can get quantitative information about 3-D images through measurement.

有关非织造土工织物滤层的几个问题的讨论

在采用了图像处理技术测定非织造土工织物的直通孔隙通道的孔隙（当量孔径）分布的新试验方法基础上，从其反滤特性和被保护土及非织造土工织物的分形维数（Ds及Dg）试验关系出发，初步总结出评价非织造土工织物滤层反滤效果的统一指标匹配关联系数α（即Dg/Ds）。它可用于选择能与既定被保护土匹配较好的非织造土工织物。

BFMT： A Simple Biometric Facial Recognition System

This study describes the development of a simple biometric facial recognition system, BFMT, which is designed for use in identifying individuals within a given population. The system is based on digital signatures derived from facial images of human subjects. The results of the study demonstrate that a particular set of facial features from a simple two-dimensional image can yield a unique digital signature which can be used to identify a subject from a limited population within a controlled environment. The simplicity of the model upon which the system is based can result in commercial facial recognition systems that are more cost-effective to develop than those currently on the market.

Iris Feature Extraction and Recognition Based on Fractal Dimension of Grayscale Extremums

This paper presented an individual recognition algorithm for human iris using fractal dimension of grayscale extremums for feature extraction.Firstly,iris region was localized from an eye image with modified circle detector stemmed from Daugman’s integro-differential operator.Then,segmentation was used to extract the iris and to exclude occlusion from eyelids and eyelashes.The extracted iris was normalized and mapped to polar coordinates for matching.In feature encoding,a new approach based on fractal dimension of grayscale extremums was designed to extract textural features of iris.Finally,a normalized correlation classifier was employed to determine the agreement of two iris feature templates,and the feature template was rotated left and right to avoid the interference from rotation of eyes and tilting of head.The experimental results show that fractal dimension of grayscale extremums can extract textural features from iris image effectively,and the proposed recognition algorithm is accurate and efficient.The proposed algorithm was tested on CASIA-IrisV3-Interval iris database and the performance was evaluated based on the analysis of both False Accept Rate(FAR)and False Reject Rate(FRR)curves.Experimental results show that the proposed iris recognition algorithm is effective and efficient.

一种基于多小波变换的自适应图像插值算法

为使插值后的图像具有很好的视觉效果和较高的信噪比,并克服使用单小波变换放大图像时的斑点干扰现象,提出了一种新颖的自适应图像插值算法,通过将图像变换到多小波域,并利用多小波域内高频子带的分形维数,自适应的根据低分辨率图像以及该图像进行一级多小波变换后的高频子带信息获取高分辨率图像二级多小波变换的子带信息,对所得到的子带信息进行二级多小波反变换,可以得到更清晰的二倍插值图像。

粗糙面分形计算理论研究进展

为提出一种工程上适用可靠的粗糙面分形维数计算方法,在分形曲线的维数计算方法(码尺法,盒维法)基础上,先后提出了星积分形曲面的维数计算方法、三角形棱柱表面积法、投影覆盖法、立方体覆盖法、改进的立方体覆盖法、分形的增变量描述法等曲面分形维数理论.鉴于上述方法的共有缺陷——获取三维坐标的激光表面仪器的扫描尺度限制,研究者提出了粗糙面图像维数计算理论,包括二值化图像维数、灰度图像维数、RGB图像维数计算理论.最后,本文展望了分形维数计算理论领域内亟待解决的三大问题.

工件粗糙度在线检测的试验研究

采用分形几何与图形图像学等交叉学科理论，基于分形布朗函数，本文提出了用于描述工件表面粗糙度的灰度图像自仿射维数计算新方法。在提出上述理论的基础上，采用高速摄像机拍摄工件车削的实时过程，计算工件的灰度图像自仿射维数，评估不同时刻工件表面粗糙度变化，进而提出可实现在线检测工件表面粗糙度的新技术。研究显示：（1）工件表面图像揭示了其表面存在清晰可见的切痕和纹理，但粗糙度不大，同时计算出的对应灰度图像自仿射维数较小，这与描述表面粗糙度的维数定义是吻合的，因而，灰度图像自仿射维数能很好地描述工件表面的粗糙度特征。（2）在初始车削不稳定状态时，灰度图像自仿射维数较大，灰度图像自仿射维数随着进刀量增加而增大，这些结论与传统检测技术所得结论是一致的，由此充分表明，本文所提的灰度图像自仿射维数计算理论是正确的，基于该理论所提的在线检测技术也是实用可行的。

Mean Curvature Flow via Convex Functions on Grassmannian Manifolds

Using the convex functions on Grassmannian manifolds, the authors obtain the interior estimates for the mean curvature flow of higher codimension. Confinable properties of Gauss images under the mean curvature flow have been obtained, which reveal that if the Gauss image of the initial submanifold is contained in a certain sublevel set of the v-function, then all the Gauss images of the submanifolds under the mean curvature flow are also contained in the same sublevel set of the v-function. Under such restrictions, curvature estimates in terms of v-function composed with the Gauss map can be carried out.