Quantitative estimation of efficiency of wavelet-processing images for single crystal structure defects

A simple procedure for quantitative estimation of the quality and efficiency of digital processing based on discrete wavelet transform (DWT) of X-ray topographic and polarization-optical images for single crystal structure defects is proposed. Digital processing of theoretical and experimental images of defects in a 6H-SiC single crystal has been performed using different wavelet types. It is shown that the brightness characteristics of the analyzed image and differential contrast may be used as a quantitative criterion of the processing quality and efficiency for the chosen wavelet. Theoretical images of typical defects in a single crystal structure calculated by the modified Indenbom-Chamrov equations have been used as a reference object.     

Defects’ geometric feature recognition based on infrared image edge detection

Edge detection is an important technology in image segmentation, feature extraction and other digital image processing areas. Boundary contains a wealth of information in the image, so to extract defects’ edges in infrared images effectively enables the identification of defects’ geometric features. This paper analyzed the detection effect of classic edge detection operators, and proposed fuzzy C-means (FCM) clustering-Canny operator algorithm to achieve defects’ edges in the infrared images. Results show that the proposed algorithm has better effect than the classic edge detection operators, which can identify the defects’ geometric feature much more completely and clearly. The defects’ diameters have been calculated based on the image edge detection results.     

基于小波分析和伪彩色处理的低对比度图像增强

提出了一种对低对比度图像进行增强处理的新技术。在对传统的伪彩色增强技术改进的基础上,将小波分析和伪彩色两种方法有机地相结合,从而克服了这两种方法的缺陷,获得了良好的增强效果。同时对实现低对比度图像增强的基本方法和基本步骤进行了详细的阐述,并将该技术应用到透视图像分析中。实验结果证明了该方法的可行性,该方法为低对比度图像增强处理提供了一种新途径。     

The study and application of a new filtering method on electronic speckle pattern interferometric fringe

It is important for the study of digital image processing to remove noises and enhance images because of various noises in images. The article is concerned with the recursive algorithm-filtering technique, which is capable of effectively removing noise and rapidly leading to a continuous gray-level distribution of a random image. By applying the method on speckle images of defects of rubber material, it is shown that this technique is the most effective and speedy method for the filtering of ESPI fringe patterns. Comparing the images before and after filtering, we can see the advantages of the novel technique clearly. It can increase the accuracy of measurement both in phase measurement and in quantitative evaluations of defects.     

基于小波变换的红外热波无损检测融合算法

在红外热波无损检测中获取的热像序列存在着背景噪声大、缺陷边缘模糊、对比度低等特点。为了提高由红外热像序列重构的数字图像的缺陷显示能力,以小波变换为热像处理工具,采用基于像素级和特征级的图像融合算法对热像序列进行了处理,并采用基于统计学的图像评估标准对处理效果作了定量评价。通过对铝合金试件的检测实验说明该方法可用于材料内部缺陷的红外热波无损检测。研究结果表明,此种图像融合算法可对不同深度缺陷所对应的两幅最佳热像进行有效地融合,在一幅融合图像中直观地反映出全部缺陷,并能有效地减少加热不均和背景噪声对缺陷识别的不利影响。     

Characterization of {111} planar defects induced in silicon by hydrogen plasma treatments

Microstructural characterization by transmission electron microscopy of the {111} planar defects induced in Si by treatment in hydrogen plasma is discussed. The {111} defects are analyzed by conventional (TEM) and high-resolution transmission electron microscopy (HRTEM). Quantitative image processing by the geometrical phase method is applied to the experimental high-resolution image of an edge-on oriented {111} defect to measure the local displacements and strain field around it. Using these data, a structural model of the defect is derived. The validity of the structural model is checked by high-resolution image simulation and comparison with experimental images.     

Wavelet processing of topographic high dynamic range images

For a 6H-SiC single crystal, experimental results of the digital processing of topographic images with various dynamic ranges are given. In this case, wavelet analysis was used. The images were obtained by x-ray topography based on the Borrmann effect and were presented in 8-, 16-, and 32-bit formats. It is shown that, on eliminating the experimental contrast granularity, 32-bit images turn out to be more convenient for decoding and contain more useful information about structure defects of a single crystal under study as compared to the 8- and 16-bit images. The wavelet analysis efficiency increases considerably for the digital processing of separate topogram fragments and depends on the choice of the region and the size of the reference image.     

Imaging of crystal defects with ballistic phonons and their three-dimensional reconstruction using digital image processing

Spatial defects in single crystals were imaged with ballistic phonons by their shadow projections using low-temperature scanning electron microscopy. Digital image recording and processing was applied for a quantitative evaluation of the experimental results. We have investigated sapphire and -quartz samples with laser-drilled holes as special model cases of crystal defects. Computer algorithms have been developed to separate the shadows of the defects from the focusing pattern in the phonon images. We obtained binary images of the structures with a typical resolution of about 20 m. Cross-correlation functions of two images were found to be well suited for image alignment procedures. By this technique and from theoretically calculated phonon intensity distributions the bolometer positions within the experimental phonon images could be determined automatically. Using two phonon detectors at different locations stereoscopical imaging of the defects became possible. From the different views the three-dimensional distribution of the defects could be calculated.     

小波图像融合在太赫兹无损检测中的应用

玻璃纤维增强复合材料被广泛应用于航天、航空及其他军民各领域,它在制备和使用过程中通常会出现多个缺陷。太赫兹时域光谱成像技术有望成为玻璃纤维增强复合材料无损检测的有力补充手段。在太赫兹时域光谱成像过程中,可以选取时域或频域波形中的不同参数来进行成像。对于不同的缺陷,能够有效地对其进行检测的参数是不一样的。采用基于小波分解的图像融合方法将多幅不同参数获取的太赫兹反射图像结合起来,得到一幅包含所有缺陷信息的新图像。研究表明,基于小波分解的图像融合方法在太赫兹无损检测中的应用,能够获取单一参数成像无法检测的缺陷信息,为复合材料太赫兹图像后期处理提供了新的技术方法。     

ARM架构下计算机图像并行化处理技术研究

为在图像处理与分析时具备良好的视觉效果,提高图像处理的速度,需要对ARM架构下计算机图像并行化处理技术进行研究。当前采用的方法是对各种变换频域图像特征提取与计算机图像集合特征的提取进行相结合,克服了当前对图像进行提取时存在图像形状描述的缺陷,提取图像特征向量维数相对较低。实验表明,通过对图像进行特征提取能很好的对图像效果进行展示,将图像的纹理特征进行详细的表述,将该方法应用到图像处理技术当中,具有良好的去噪效果及扩展性,该方法过程简单,但存在图像视觉效果较差的问题。为此,提出一种ARM架构下计算机图像并行化处理技术研究方法。该方法首先利用非局部均值去噪算法对图像进行去噪处理,然后结合图像去噪的结果利用小波变换对去噪图像进行边缘检测,最后采用非线性增强算法对图像进行增强完成对ARM架构下计算机图像并行化处理技术研究。实验结果表明,所提方法不仅提高图像处理速度,还提高图像视觉效果,具有广泛的应用价值。     

光学元件表面缺陷的显微散射暗场成像及数字化评价系统

根据国际ISO10110-7的表面缺陷标准及惯性约束聚变(ICF)工程标准,提出了一种新颖的光学元件表面缺陷的光学显微散射成像及数字化评价系统,多束光纤冷光源呈环状分布并以一定角度斜入射到数毫米视场的被检表面,形成适合数字图像二值化处理的暗背景上的亮疵病图像。对X,Y两方向进行子孔径图像扫描成像,利用模板匹配原理对获得的子孔径图像进行拼接得到全孔径表面疵病图像信息。基于数学形态学建立了可用于大口径表面检测扫描的图像处理的模式识别软件体系,并应用二元光学制作了标准对比板,以获得疵病正确的评价依据。最终利用该变倍光学显微镜散射成像系统得到能分辨微米量级表面疵病的图像,其单个子孔径物方视场约为3 mm,对X,Y两方向进行5×5子孔径图像扫描成像,并给出了与标准比对的定量数据结果。实验结果表明,本系统完全可以实现光学元件表面缺陷的数字化评价。     

闪光照相图像缺陷消除方法

 介绍了一种检测闪光照相图像缺陷以及消除这些缺陷的方法。在闪光照相实验中,底片图像会出现一些小尺寸的缺陷影响了底片信息的精确提取。根据闪光照相实验中采用完全一样的多张底片接收的特点,提出了一种闪光照相多底片图像的缺陷消除方法。首先对这些底片图像进行精确配准,将这些图像进行简单平均以获得均值图像,利用均值图像与各底片图像的差值获得缺陷图像,然后根据缺陷图像的特点对缺陷进行分割并判断各缺陷的归属。最后根据均值图像与缺陷图像以及缺陷分割与判断结果获得修补后的底片图像。实验结果证明该方法可以有效地消除多底片图像中的各类缺陷。     

一种基于2D-CNN的激光超声表面缺陷检测方法

激光超声表面缺陷检测的过程中,缺陷的定量表征通常依赖于操作者的判断,易受到人为因素干扰,致使检测结果不稳定。针对这一问题,提出一种基于图像识别的二维卷积神经网络（2D-CNN）的缺陷自动分类检测方法。利用有限元方法模拟激光超声检测过程,并采集超声信号数据用于训练分类模型;使用连续小变换（CWT）处理超声信号得到小波时频图,以小波时频图作为输入训练卷积神经网络（CNN）分类模型,实现对表面缺陷深度的自动分类。验证结果表明:提出的检测方法能够对不同深度的缺陷准确分类,测试的平均准确率达到97.3%;构建的CNN分类模型能够自主学习输入图像的缺陷特征并完成分类,提高了检测结果稳定性,为激光超声缺陷检测的自动化分析处理提供了新的思路。     

基于ICT切片图像相邻层信息的缺陷自动识别方法

 现有的工业计算机断层成像（ICT）图像缺陷识方法中,多采用对单张图像进行孤立评判方法,此类方法未能考虑到单张图像在相邻层图像信息关联性,因而易将孤立的噪音视为缺陷,造成误判。为解决这一问题,提出一种基于序列ICT切片图像自动识别方法,该方法将识别过程分为两步：单张图像的潜在缺陷提取和相邻层图像缺陷的匹配。第一步运用传统方法识别出每张图像中所有潜在缺陷;第二步根据真缺陷在相邻层具有匹配关系而伪缺陷则相对孤立的特点,通过分步匹配的方法确定每张图像上所有潜在缺陷在相邻层图像上的匹配关系,区分出真伪缺陷。最后通过实例验证表明：利用该方法可以有效得提高真缺陷得识别率,降低误判率。     

基于YOLOv3框架的高分辨电镜图像原子峰位置检测

高分辨电镜图像中原子峰位置的检测具有十分重要的现实意义,通过精确定量化原子峰位置可以分析物质在微观尺度上的结构形变、电极化矢量分布等重要信息.近年来深度学习技术在图像目标检测领域取得了巨大突破,这一技术可用在高分辨电镜图像处理上,因为原子位置的检测可以看作是一个目标检测问题.本文利用先进的机器学习方法,通过制作高质量原子图像样本集,使用YOLOv3目标识别框架对原子图像进行自动检测,达到预期效果,实现了深度学习技术在高分辨电镜图像处理领域的应用.该方法的运用有望突破自动处理动态、大量电镜图片的瓶颈问题.     

基于频域纹理消除的结构性纹理缺陷检测方法

针对金属加工表面等结构纹理表面图像缺陷检测问题,结构纹理的存在会对缺陷（比如划痕）检测带来干扰,该文开展在频率域中消除背景纹理的方法来进行缺陷检测的研究。首先基于傅里叶变换的图像复原技术,空间域图像中的结构性纹理对应傅里叶域中高能频率分量,使用最小二乘法直线拟合操作去除,并将这些能量设置为零,经傅里叶逆变换为空间域图像。在复原的图像中,原始图像中的结构纹理区域将变为近似的均匀灰度级,但其中缺陷部分将被保留下来。再使用统计过程控制来设置阈值的方法就能从复原图像中分离出缺陷。最后在一系列的结构性纹理图像上的实验证实了所提方法可行且有效。     

Study on inspection method of glass defect based on phase image processing

To solve the problem in projecting grating method, the paper presents an inspection method based on phase image processing for glass defects. In the proposed method, the wrapped phase difference is achieved according to the images of defect-free and defect-containing. The unwrapping phase algorithm, based on jump corrected is used to eliminate jump error. The segmentation of defect region is implemented by integrating grayscale mathematical morphology with high-low threshold segmentation, and the boundary coordinate of connected region is used to calculate the size and location of defect. The results demonstrate that the proposed method provides reliable identification of defects.     

A novel method for identification of cotton contaminants based on machine vision

Foreign matter is easily mixed into cotton during picking, storing, drying, transporting, purchasing, and processing. These contaminants are difficult to remove in the spinning process and can cause yarn breakage, thus reducing efficiency of working. This paper proposed the new method based on machine vision to measure the contaminants in raw cottons. The color images of cottons with contaminants are acquired and divided three channels images. Intensity of illumination of cottons often is unstable because of the driving voltage of light source unsteady. The intensity of illumination of images should be corrected for measuring correction and precision. The Gamma adjustment function was adopted to correct non-uniform illumination for images. Through the experimental contrast, Gamma correction parameter is set as 0.8. The Otsu method is used to segment the image. After images of three channels’ information fusing, the contaminants of cotton samples can be correctly detected and cotton seeds also can be effectively inspected. The false detection ratio of the measuring system is less than 5%. The experimental results show the measuring system can meet with the requirement of the cotton's industry application.     

多帧融合处理技术在运动模糊图像复原中的应用

运动模糊图像是电视监控中常见的退化图像 ,也是图像处理和检验工作中的难题。针对电视摄像的特点 ,多帧融合处理技术从图像时间序列中提取景物的运动信息 ,构造复原滤波器 ,通过频率域反转滤波方式复原模糊图像。这项技术能够有效地增强电视监控中存在的运动模糊图像 ,并且适用于数字视频图像处理     

Split bregman method-based background extraction for blob-mura defect detection in thin film transistor-liquid crystal display image

In this paper, we present the results of using a split Bregman method for blob-Mura defect detection in a thin-film transistor-liquid crystal display (TFT-LCD) image. A reference image obtained by the split Bregman method was simply subtracted from a test image to detect blob-Mura defects. For a test image, two resulting images containing black or white bob-Mura defects were obtained separately. Through simulation it was verified that the proposed method has a superior capability for detecting blob-Mura defects.