A study of the dependence of wavelet-transform coefficients on the geometrical parameters of discontinuity flaws

The dependence of the wavelet-transform coefficients of the magnetic field of a continuity flaw in a ferromagnetic article on its geometrical dimensions is theoretically and experimentally studied.     

Dependence of the cutting energy on the parameters in superfinishing

Analysis of the energy consumption when using different types of abrasive bars permits the derivation of a dependence of the cutting energy on the machining conditions.     

不同角度下马铃薯多光谱图像的植叶面积提取

为了更好地研究马铃薯光谱特性,对马铃薯植株的植叶面积进行了探究。采用Spectrocam多光谱相机对光以不同照射角度照射下的植叶面积进行数据采集,并运用软件对数据进行二值化处理和亮度处理。实验结果表明,在中心波长为750nm和800nm的通道下,计算出的马铃薯植叶面积差异不大,但是将两者的二值图与原图进行细节对比,中心波长为800nm的通道的二值图与原图较为吻合,所以中心波长为800nm的通道是计算马铃薯植叶面积的最优通道。     

Assessing test results on the basis of acoustic images

General concepts of the construction of tomographic images generated by systems via coherent data processing are discussed. Characteristic features of the images are analyzed.     

Dependence of the recovery parameters of objects on the characteristics of the recovery process

For the main recovery parameters of an object, the formulas of their dependence on the recovery process characteristics have been proved. The established dependences are nonparametric and, thus, applicable to the arbitrary laws of the recovery process of objects.     

Automatic segmentation of diatom images for classification

A general framework for automatic segmentation of diatom images is presented. This segmentation is a critical first step in contour-based methods for automatic identification of diatoms by computerized image analysis. We review existing results, adapt popular segmentation methods to this difficult problem, and finally develop a method that substantially improves existing results. This method is based on the watershed segmentation from mathematical morphology, and belongs to the class of hybrid segmentation techniques. The novelty of the method is the use of connected operators for the computation and selection of markers, a critical ingredient in the watershed method to avoid over-segmentation. All methods considered were used to extract binary contours from a large database of diatom images, and the quality of the contours was evaluated both visually and based on identification performance.     

Mathematical classification of tight junction protein images

We present the rationale for the development of mathematical features used for classification of images stained for selected tight junction proteins. The project examined localization of zonula occludens‐1, claudin‐1 and F‐actin in a model epithelium, Madin–Darby canine kidney II cells. Cytochalasin D exposure was used to perturb junctional localization by actin cytoskeleton disruption. Mathematical features were extracted from images to reliably reveal characteristic information of the pattern of protein localization. Features, such as neighbourhood standard deviation, gradient of pixel intensity measurement and conditional probability, provided meaningful information to classify complex image sets. The newly developed mathematical features were used as input to train a neural network that provided a robust method of individual image classification. The ability for researchers to make determinations concerning image classification while minimizing human bias is an important advancement for the field of tight junction cellular biology.     

基于形态特征判别超声图像中乳腺肿瘤的良恶性

乳腺肿瘤超声图像的形态特征对判别肿瘤的良恶性具有重要的价值。为提高乳腺肿瘤超声诊断的准确率,提出一种基于其形态特征进行分类判别的计算机辅助诊断系统。该系统首先采用灰度阈值分割和动态规划相结合的方法提取超声图像中乳腺肿瘤的边缘,然后对所得边缘计算相应的三种形态参数,最后分别采用Fisher线性判据、误差反向传播神经网络和径向基函数神经网络对形态参数进行分类。该系统在157幅乳腺肿瘤(包括良性81例、恶性76例)超声图像上训练和测试,三种分类器均能取得较高的判别精度,其中误差反向传播神经网络和径向基函数神经网络的判别准确率、敏感性和特异性分别高达94.95 %、95.74%和94.23%。结果表明,基于乳腺肿瘤超声图像的形态特征建立的神经网络系统对肿瘤的良恶性具有较好的判别能力。     

基于多尺度特征融合的遥感图像场景分类

为了解决遥感图像场景分类中因样本量小而分类精度不高的问题,提出了一种基于多尺度特征融合(MSFF)的分类方法。首先,对遥感图像进行尺度变换,得到同一遥感源图像的多个不同尺度图像。接着,将其分别输入深度卷积神经网络(DCNN)中进行卷积操作。然后,将各卷积层和全连接层提取出的不同尺度特征进行降维和编码/平均池化操作。最后,将各尺度特征进行编码融合并利用多核支持向量机(MKSVM)进行场景分类。在两个公开遥感图像数据集UCM Land-Use和NWPU-RESISC45中进行试验,分类精度最高分别达到98.91%和99.33%。本文方法能够利用不同尺度的图像特征,结合低、中、高层语义表示,使融合特征的可辨识性更高,同时使用多核支持向量机提高了深度网络学习的泛化能力,因此分类效果更好。     

Underwater cable detection in the images using edge classification based on texture information

In this paper, a new approach is proposed for detection of an underwater cable, which makes an Autonomous Underwater Vehicle (AUV) capable for automatic tracking. In this approach instead of traditional image segmentation, first, edges of the images are extracted. Then they are classified using Multilayer Perceptron (MLP) neural network and Support Vector Machine (SVM) using texture information. Then the edge points belonged to the background information are removed and the remaining ones are used for the next processes. Finally, the filtered edges are repaired by morphological operators and are fed into the Hough transform for cable detection. Some texture information methods are used for feature extraction but the results confirm that the 2D Fourier transform in combination with MLP network is the best method for edge classification in this environment. Hough transform, is used in two strategies, which in the first one, the whole information of the edges in the image, are used for line detection, and in the second approach because of curve like shape of the cable, a center part of the image, is used for line detection. In the experiments, many different scenes was used for testing the cable detection algorithm, which first method, resulted to good accuracy but the second one, provided better recognition rate for the cable detection task.     

运动模糊图像点扩展函数的参数鉴别

为了更加准确地鉴别出运动模糊图像的点扩展函数参数,提出了一种在倒谱域鉴别模糊参数的方法。该方法通过对运动模糊图像的倒谱图实施灰度变换,运用Canny边缘检测精确提取出倒谱,进而计算出运动模糊的尺度;对倒谱实施RADON变换确定运动模糊的方向。对130幅不同模糊程度的计算机仿真图像和相机实拍的图像鉴别结果表明:该方法鉴别PSF参数准确,且具有较强的鲁棒性。使用鉴别出的PSF参数,运用维纳滤波对运动模糊图像进行了复原,复原结果也证实了本方法鉴别PSF参数的有效性和准确性。     

Automated classification and visualization of fluorescent live cell microscopy images

Robotic, high‐throughput microscopy is a powerful tool for small molecule screening and classifying cell phenotype, proteomic and genomic data. An important hurdle in the field is the automated classification and visualization of results collected from a data set of tens of thousands of images. We present a method that approaches these problems from the perspective of flow cytometry with supporting open‐source code. Image analysis software was created that allowed high‐throughput microscopy data to be analysed in a similar manner as flow cytometry. Each cell on an image is considered an object and a series of gates similar to flow cytometry is used to classify and quantify the properties of cells including size and level of fluorescent intensity. This method is released with open‐source software and code that demonstrates the method's implementation. Accuracy of the software was determined by measuring the levels of apoptosis in a primary murine myoblast cell line after exposure to staurosporine and comparing these results to flow cytometry.     

Retrieving modulation parameters from HRTEM images of modulated structures

Quantitative high-resolution transmission electron microscopy (qHRTEM) is methodologically extended towards the assessment of occupationally and positionally modulated structures. For this purpose, iterative digital image matching has been combined with data processing within the Rietveld refinement code JANA2000. In this approach, the number of free parameters is kept low and rather complicated modulated structures become assessable by qHRTEM. The feasibility of the improved methodology is demonstrated for the 1D modulated structure of Ba(2)TiGe(2)O(8).     

Determination of the important machining parameters on the chip shape classification by adaptive neuro-fuzzy technique

The main goal of the study was to analyze the influence of machining parameters on the chip shape classification. Straight turning of mild steel (A500/A500M-13) and AISI 304 stainless steel were performed to monitor the chip shapes. Cutting speed, feed rate, depth of cur and surface roughness of the material were used as inputs. Adaptive neuro-fuzzy inference system (ANFIS) was used in to determine the inputs influence on the chip shape classification. The selection process was performed to estimate the most dominant factors which affect the chip shape classification. According to the results surface roughness has the highest influence on the chip shape classification. The obtained model could be used as optimal parameter settings for the best chip shape classification.     

Characterization of shapes for use in classification of starch grains images

As tradition Chinese herbal medicine becomes increasingly popular, there is an urgent need for efficient and accurate methods for the authentication of the Chinese Materia Medica (CMM) used in the herbal medicine. In this work, we present a denoising filter and introduce the use of chord length distribution (CLD) for the classification of starch grains in microscopic images of Chinese Materia Medica. Our simple denoising filter is adaptive to the background and is shown to be effective to remove noise, which appears in CMM microscopic starch grains images. The CLD is extracted by considering the frequency of the chord length in the binarized starch grains image, and we shall show that the CLD is an efficient and effective characterization of the starch grains. Experimental results on 240 starch grains images of 24 classes show that our method outperforms benchmark result using the current state-of-the-art method based on circular size distribution extracted by morphological operators at much higher computational cost.     

Dependence of the measured size of the objects on the parameters of the transmitted light source in video measurement microscopy

Parameter adjustment of the transmitted light source yields a good‐quality image for video measurement microscopy. However, a disadvantage is that the measured size of the objects changes simultaneously while the parameters of the transmitted light source are adjusted, which directly affects the measurement accuracy adversely. Furthermore, the variation of the objects’ measured size leads to the magnification variation as well. In order to analyse how the measured size of the objects varies with the parameters, we apply a photometric method and an operator algebra method to derive a unified mathematical model that correlates the parameters of the transmitted light source with the measured size of the objects. Theoretical results show that factors including the illumination intensity, the diameter of the aperture stop and the field stop and the object thickness are important to the measured size of the objects. The simulation results have been verified thoroughly using a wide variety of internal and external diameter measurement experiments. The proposed method has proved to be suitable to determine how these parameters affect measured size of the objects.     

采用非采样Contourlet变换与区域分类的红外和可见光图像融合

提出基于多尺度变换和区域相结合的红外与可见光图像融合方法,用于有效保留红外图像与可见光图像中的空间信息及热目标信息,提升融合图像的可观测性和可理解性。首先,基于非采样Contourlet变换(NSCT)方法对红外和可见光图像进行初步融合,采用基于局部能量的规则融合低通子带系数,根据尺度内各方向子带的相关性原则融合带通方向子带系数。然后,计算初次融合后所得的融合图像与源图像的结构相似性(SSIM),根据源图像与初次融合图像的结构相似程度对图像进行区域分类,得到相似区域分类标识图。最后,依据区域内各自的相似度特性,分别采用不同的融合策略进行二次融合,从而得到最终的融合结果。实验结果表明:该方法能够充分提取源图像的区域特征和纹理特征,融合结果在主观和客观评价上均优于目前流行的融合方法。与仅使用NSCT法进行融合相比,实验所采用的两组图像的质量评价指标分别提高了16%、85%、54%、36%和18%、102%、84%、41%。表明该方法在主客观评价上均优于双树复杂小波变换(DTCWT)、NSCT、冗余离散小波变换(RDWT)等方法。     

On the influence of some test parameters on the results of oscillating sliding tests

The friction and wear behaviour of materials is often characterised in laboratory tests using a simple ball-on-flat configuration. From this type of test can be derived information useful in guiding the development of tribomaterials and in helping select candidate materials for specific applications. A large variety of tribotesting methods exists, and indeed several are not yet standardised. One of these methods is the oscillating sliding test, where a ball moves in relation to a disc, usually with small strokes. This method is almost non-destructive and can be applied to very small specimens. One of the most important parameters in laboratory tests is the humidity of the surrounding air. Experimental results on the friction and wear characteristics of different ceramics tested against different ball materials at room temperature in oscillating sliding contact are presented here and discussed, taking into account the effects of the test duration, relative humidity, and counterbody material.