Edge detection,three-dimensional cell boundary reconstruction and volume and surface area estimation from differential interference contrast images

Three-dimensional (3-D) cell morphology is important for the understanding of cell function and can by quantified in terms of volume and surface area. Differential interference contrast (DIC, or Nomarski) imaging can enable cell edges to be clearly visualized in unstained tissue due to the slight difference in refractive index between aqueous media and cytoplasm. DIC is affected in only one direction - the direction of the optical shear. A 1-D edge detector was used in that direction with a scale length equal to that of an in-focus edge to highlight cell boundaries. By comparison with the signal from the edge detector on an out-of-focus slice, the in-focus slices could be segmented and, after noise suppression, cell outlines obtained. A voxel paradigm was used to calculate cell volume and differential geometry was used for surface area estimation. We applied this approach to obtain 3-D dimensional information by optical sectioning of motile Amoeba proteus.     

基于序列局部图像的尺寸高精度测量方法

为实现大尺寸机械零件的高精度视觉测量,研究基于序列局部图像的视觉测量方法。首先分析机械零件图像边缘的过渡分布特征,提出边缘像素补偿法,消除实际边缘不能精确定位对测量精度的影响。然后以直线边缘距离测量为原型,提出基于序列局部图像尺寸特征的测量方法：对零件进行微小区域成像,生成在空间上连续的序列局部图像;应用相关系数法和双线性插值法获得相邻序列图像的亚像素级尺寸特征线,从而得到各局部图像的尺寸特征;对这些尺寸进行求和与补偿,得到零件的总体尺寸。实验表明,对常规尺寸零件的单幅图像运用边缘像素补偿法,相对测量误差在0.008%以内;对大尺寸零件应用序列图像测量法,相对测量误差在0.01%以内,具有误差积累小的优点,可用于机械零件的精密自动化测量。     

应用Canny算法和灰度等高线的金相组织封闭边缘提取

为了对金相组织的多项组织含量进行定量分析,提出应用Canny算法和灰度等高线相结合的方法来产生封闭金相组织边缘。首先,采用高斯函数对金相组织的灰度图像进行模糊处理,然后,用Canny算法对模糊后的图像获取具有单边缘效应的原始边缘。通过最大类间方差法对原始边缘进行自动计算,获得抑制虚假边缘的阈值,并通过该阈值获取基础边缘。由于基础边缘具有不连续性,因此需根据基础边缘端点的邻域灰度中值计算所需的灰度等高线,同时根据设定的等高线和基础边缘融合的条件,以基础边缘的端点为起点生成封闭边缘。实验结果表明,该算法可有效地生成符合要求的封闭边缘,采用该算法产生的封闭边缘进行金相组织含量测定可使测量误差降低到±1%,可测组织含量范围达到5%～95%。该算法能满足多项金相组织含量测定的定量分析要求且具有普适性。     

Segmentation of ascidian notochord cells in DIC timelapse images

We have developed a method to automatically segment notochord cell boundaries from differential interference contrast (DIC) timelapse images of the elongating ascidian tail. The method is based on a specialized parametric active contour, the network snake, which can be initialized as a network of arbitrary but fixed topology and provides an effective framework for simultaneously segmenting multiple touching cells. Several modifications to the original network snake were necessary for high-quality segmentation, including linear Gaussian derivative filtering to reconstruct edge maps from DIC images and a new energy function to improve the segmentation of critical cell-cell vertices. We find that post-intercalation ascidian notochord cells exhibit two distinct cell behaviors: lateral cell edges expand along the AP axis while showing a rapid pulsatile behavior, whereas anterior and posterior cell edges contract smoothly.     

Utilizing confocal microscopy to measure refractive index of articular cartilage

This study proposes a method for measuring the refractive index of articular cartilage within a thin and small specimen slice. The cartilage specimen, with a thickness of about 50 μm, was put next to a thin film of immersion oil of similar thickness. Both the articular cartilage and immersion oil were scanned along the depth direction using a confocal microscope. The refractive index mismatch between the cartilage and the immersion oil induced a slight axial deformation in the confocal images of the cartilage specimen that was accurately measured by a subpixel edge‐detection‐based technique. A theoretical model was built to quantify the focal shift of confocal microscopy caused by the refractive index mismatch. With the quantitative deformations of cartilage images and the quantified function of focal shift, the refractive index of articular cartilage was accurately interpolated. At 561 nm, 0.1 MPa and 20 °C, the overall refractive index of the six cartilage plugs was 1.3975 ± 0.0156. The overall coefficient of variation of all cartilage specimens was 0.68%, which indicated the high repeatability of our method. The verification experiments using distilled water showed a minimal relative error of 0.02%.     

一种彩色印刷图像套印检测新方法研究

提出了一种印刷品检测方法,用印刷图像信息取代套印控制条来检测套准。首先,把CCD采集到的印刷品图像从RGB色彩空间转换到CMYK色彩空间,并分解成C、M、Y、K(青、品、黄、黑)4个通道。之后求出C、M、Y、K通道图像的边缘,计算C、M、Y边缘图像和基准K边缘图像的距离边缘共生矩阵(distance edge cooccurrence matrix,DECM),即可求出四色套印偏差。通过仿真和实验证明本算法检测印刷品套准具有较高的精度,符合国家印刷行业标准规定的套准精度要求。为印刷机的工作状态的调整提供可靠的数据。     

模糊图像边缘精确定位的滤波算法

图像的边缘是图像最基本也是最重要的特征之一。实际应用中,光学系统离焦和图像传感器噪声源引起图像模糊,导致边缘自动定位算法无法精确确定边缘点。从边缘检测理论出发,根据噪声及图像模糊模型,提出了基于空间域和频域的滤波方法对模糊边缘图像去噪,从而消除模糊图像对于边缘定位的影响。实验表明,各种滤波方法对于边缘点的自动提取都具有一定的效果,离焦模糊和噪声可以得到有效抑制,尤其是频域低通滤波器能够精确地提取出模糊边缘位置。     

Improvement of overlapping nuclear track densitometry

Detection of tracks produced by α particles, protons or nuclear fission fragments in plastic detectors, viz., solid‐state nuclear track detectors, constitutes a very important tool in various areas. It is not easy for humans to count CR‐39 nuclear tracks manually, especially when the track density is very high. An automated computer program called KTTMS2, written in C++ and running with a user friendly interface, has been developed for recognition and parametric measurements of etched tracks in images captured from the surface of solid‐state nuclear track detectors. Well‐known edge detection methods were applied to estimate the precision and accuracy of nuclear track densitometry using the CR‐39 detector. Among the various routine edge detection methods, the Canny method was chosen because it was the most accurate technique. Because accuracy becomes more important as the track density increases, this allows more overlapping tracks to be detected. KTTMS2 (the proposed system) has an efficiency of 95% and can identify the noise as a background track (5%). Experimental results showed that the error percentage was reduced from 7.63% to 3.23% for high‐density tracks when the count was adjusted by the estimated overlapping tracks.     

重轨图像增强与边缘提取的关键技术

针对重轨图像两个边缘像素特征不一致,传统边缘算子检测法难以精确提取边缘的问题,提出了一种新的边缘提取方法.该方法利用灰度强对比度拉伸算法对重轨表面和背景进行差异化拉伸增强边缘信息,削弱背景信息.运用最大方差比算法选取增强后图像的最佳阈值实现二值化.最后,运用递归连通域标识法定位边缘像素坐标,完成图像分割.对随机选取的30幅图像进行分析表明:处理后的图像边缘灰度特征明显增强,有效地抑制了表面纹理及虚假边缘.重轨表面像素宽度波动减少到-0.64％～0.34％.离散预处理算法通过遍历寄存器全局数组,减少分割时间至10.165 s.该方法在抗干扰性、准确性及时效性等方面优于传统边缘算子检测法,适用于在线工业检测系统.     

Three-dimensional volume reconstruction of extracellular matrix proteins in uveal melanoma from fluorescent confocal laser scanning microscope images

The distribution of looping patterns of laminin in uveal melanomas and other tumours has been associated with adverse outcome. Moreover, these patterns are generated by highly invasive tumour cells through the process of vasculogenic mimicry and are not therefore blood vessels. Nevertheless, these extravascular matrix patterns conduct plasma. The three‐dimensional (3D) configuration of these laminin‐rich patterns compared with blood vessels has been the subject of speculation and intensive investigation. We have developed a method for the 3D reconstruction of volume for these extravascular matrix proteins from serial paraffin sections cut at 4 µm thicknesses and stained with a fluorescently labelled antibody to laminin ( Maniotis et al., 2002 ). Each section was examined via confocal laser‐scanning focal microscopy (CLSM) and 13 images were recorded in the Z‐dimension for each slide. The input CLSM imagery is composed of a set of 3D subvolumes (stacks of 2D images) acquired at multiple confocal depths, from a sequence of consecutive slides. Steps for automated reconstruction included (1) unsupervised methods for selecting an image frame from a subvolume based on entropy and contrast criteria, (2) a fully automated registration technique for image alignment and (3) an improved histogram equalization method that compensates for spatially varying image intensities in CLSM imagery due to photo‐bleaching. We compared image alignment accuracy of a fully automated method with registration accuracy achieved by human subjects using a manual method. Automated 3D volume reconstruction was found to provide significant improvement in accuracy, consistency of results and performance time for CLSM images acquired from serial paraffin sections.     

采用子图像抽取尺度变换的边缘检测方法

针对工业尺寸检测中现场采集图像模糊但目标占有空间尺度较大这一特点,利用低分辨率采样下图像高频特征失真较大而低频特征失真较小的原理,提出了一种通过图像抽取获得多幅不同尺度子图像分别进行边缘检测后,综合各子图像边缘与原图像边缘来提取大尺度弱边缘的算法。试验结果表明,本算法能有效地检测出图像中的大尺度弱边缘。     

Quantifying cell–matrix adhesion dynamics in living cells using interference reflection microscopy

Focal adhesions and podosomes are integrin‐mediated cell‐substratum contacts that can be visualized using interference reflection microscopy (IRM). Here, we have developed automated image‐processing procedures to quantify adhesion turnover from IRM images of live cells. Using time sequences of images, we produce adhesion maps that reveal the spatial changes of adhesions and contain additional information on the time sequence of these changes. Such maps were used to characterize focal adhesion dynamics in mouse embryo fibroblasts lacking one or both alleles of the vinculin gene. Loss of vinculin expression resulted in increased assembly, disassembly and/or in increased translocation of focal adhesions, suggesting that vinculin is important for stabilizing focal adhesions. This method is also useful for studying the rapid dynamics of podosomes as observed in primary mouse dendritic cells.     

基于导向滤波Retinex和自适应Canny的图像边缘检测

机器视觉识别常用金属制品边缘时,表面亮度不均易导致边缘误识别,且传统的边缘检测算法去噪的同时也抑制了大量边缘信息,降低了边缘检测质量。本文提出一种基于导向滤波Retinex和自适应Canny的图像边缘检测算法。该算法采用基于导向滤波的Retinex法得到金属制品图像的反射分量,通过加权分布的自适应伽马校正提升反射分量图像对比度;然后,采用自适应各向异性扩散滤波对增强后图像进行去噪处理,抑制增强后图像的噪声及低对比度纹理,再采用改进四方向Sobel梯度模板提取图像边缘;最后沿用传统Canny算法的非极大值抑制及双阈值分割进一步细化边缘。实验结果表明,新算法检测典型金属小零件时,图像锐度指标由原图的47.11提升至68.39,金属表面的亮度标准差从原图的44.76下降至20.16;噪声指标从原图的1.1下降到0.15左右,并且在去噪的同时较好地保留了图像边缘锐度。新方法有效改善了金属表面图像因亮度不均导致的边缘误识别问题,并且提取的边缘连接性较好。     

广角天文望远镜的自动调焦

介绍了一种基于步进电机(无位置检测传感器)和像质反馈的广角天文望远镜自动调焦系统,该系统由步进电机位置开环控制系统和图像清晰度评价系统组成。基于天文图像的特点,提出利用天体点源星像的半高全宽(FWHM)作为图像清晰度的评价参数;为了提高系统精度,对定位控制系统进行了误差分析;测定了调焦当量、光学焦深、系统回差、步进脉冲当量等系统关键机构参数,进而高精度地修正了系统定位误差;分析和测定了温度变化和像质变化的相关性,明确了调焦方向和温度变化之间的定性关系;设计了焦深边缘定位策略,实现了快速调焦。该系统具有"容错"和"自学习"功能,具有较高的自动化和智能化程度。将系统设计应用于SVOM天文卫星地基广角相机阵[1-2](GWAC),实际测试和天文观测表明,调焦系统的定位精度为±3.0μm,调焦精度为0.05pixel,且一次调焦过程即可获得最佳像质,调焦效率较高,系统运行也很稳定,基本满足天文观测的需求。     

基于小波变换和形态学的图像边缘检测方法

提出了一种基于小波变换和形态学的图像边缘检测方法。对源图像进行小波分解,用数学形态学法对低频子图像进行边缘检测,用小波变换法提取高频图像的边缘,采用一定的融合规则将两个边缘图像融合在一起得到一幅完好的边缘图像。这种边缘检测方法结合了小波变换法和数学形态学法的优点,对用这两种方法得到的边缘信息进行融合,有效地抑制了噪声,且边缘连续、清晰。实验结果表明,提出的这种结合方法优于单独使用数学形态学法或小波变换法。     

DIC image reconstruction on large cell scans

The width of the emission spectrum of a common fluorophore allows only for a limited number of spectral distinct fluorescent markers in the visible spectrum, which is also the regime where CCD-cameras are used in microscopy. For imaging of cells or tissues, it is required to obtain an image from which the morphology of the whole cell can be extracted. This is usually achieved by differential interference contrast (DIC) microscopy. These images have a pseudo-3D appearance, easily interpreted by the human brain. In the age of high throughput and high content screening, manual image processing is not an option. Conventional algorithms for image processing often use threshold-based criteria to identify objects of interest. These algorithms fail for DIC images as they have a range from dim to bright with an intermediate intensity equal to the background, so as to produce no clear object boundary. In this article we compare different reconstruction methods for up to 100 MB-large DIC images and implement a new iterative reconstruction method based on the Hilbert Transform that enables identification of cell boundaries with standard threshold algorithms.     

船体零件几何尺寸测量图像分割方法研究

针对船体零件表面划痕、锈蚀以及下表面成像等因素导致的伪边缘及边缘不连续问题,提出了基于边缘与 k-means 聚类的船体零件图像分割方法.对于表面划痕及锈蚀形成的伪边缘,在矩形边缘检测区域内利用轮廓法线方向与边缘梯度方向信息予以剔除;零件下表面成像导致的伪边缘,选取 k-means聚类区分零件的上下表面边缘;边缘不连续问题,基于测地距离和断点方向准确连接断点,形成封闭轮廓.实验结果表明,使用该方法可获得平滑、封闭的分割效果,船体零件的几何尺寸测量误差低于 ０.５mm ,且测得量值标准偏差的平均值为 ０.２６２mm ,测量重复性较高,有效保障了船体零件几何尺寸的测量精度.     

基于非线性扩散滤波的边缘检测和图像测量

提出了一种基于自适应非线性扩散方程滤波的边缘检测方法, 以提高图像测量的精度。首先对原始图像实施一种非线性扩散处理,即沿着等照度线(边缘)的梯度方向实施反向扩散以锐化边缘, 而相反地沿切线方向实施正向扩散以去除噪声和锯齿伪像; 然后应用经典的微分算子来检测边缘。实验结果表明,相对于经典的边缘检测算子, 本算法得到了尖锐而平滑的单像素宽的图像边缘,较好地定位了边缘, 相对误差为0.03。当图像边缘模糊和存在附加噪声时, 测量结果将会受到很大影响。本方法较好地定位了边缘像素, 对于微小尺寸测量显示出它的优越性.     

飞机三维姿态测量的角平分线方向向量法

基于交会测量提出了一种飞机三维姿态测量的新方法—角平分线方向向量法。对交会图像进行边缘检测和特征线提取,获得飞机两机翼边缘特征线上适当两点的坐标,经两次坐标转换到特定坐标系下;联合经纬仪参数及跟踪的俯仰、方位角,解算机翼边缘特征线在特定坐标系下的方向向量,利用飞机结构的对称性,在机翼特征线平面求解其两条角平分线方向向量;重构飞机中轴线及其同面垂线的方向向量;据此计算出飞机的俯仰、偏航和滚动三维姿态。利用两台光电经纬仪交会跟踪飞机的眼镜蛇机动飞行表明提出的方法稳定、实用,只要图像上机翼边缘线成像清晰,测量的姿态角误差不会超过1°。此方法不仅可为靶场光测设备跟踪图像的处理提供一种新途径,而且可为其他运动目标的姿态测量提供借鉴。     

旋转机械参数图形多尺度多结构元边缘检测

以旋转机械振动信号参数图形为研究对象,在600 MW模化汽轮机转子试验台上完成了转子正常、转子不对中和轴承松动故障的实验研究,得到了相应的振动参数三维图形。对不同故障的振动参数三维图形进行了二维灰度转化及图形预处理;依据多尺度滤波增强处理方法滤除了参数图形的噪声,增强了有用信息;利用多结构元边缘检测算子对参数图形进行了边缘检测。结果表明：多尺度多结构元边缘检测方法抗噪能力强,能够在滤除旋转机械振动信号参数图形中噪声的同时,有效地提取图形的边缘特征,适用于环境噪声较为复杂的旋转机械状态监测。