图像处理技术在面包烘焙品质检验中的应用

阐速了数字图像处理技术在烘焙面包品质检验中的应用,依据灰度共现矩阵算法提取图像的纹理特征,并通过二值化后的烘焙面包切片计算出其体积。试验结果表明,该方法不仅为面包烘焙品质的快速自动检验提供了客观准确的科学依据,使感官评价的指标客观化,而且经济可行。     

基于彩色Gabor特征的人脸识别技术

提出了一种利用所提取的彩色Gabor特征来提高人脸识别系统性能的方法。首先利用四元数表示彩色信息,考虑到Gabor滤波器具有空间局部性和方向选择性的特点,将其扩展到四元数空间。然后通过人脸图像特征点与Gabor滤波器的卷积来提取特征,这样就将传统的灰度Gabor特征拓展为彩色Gabor特征。最后对于所提取的特征利用PCA降维后送入支持向量机中分类。实验采用彩色FERET人脸库并利用ROC曲线进行交叉检验,结果说明通过提取和利用这种彩色纹理信息能显著提高人脸识别系统性能。     

协同分布式图形硬件的混合并行体绘制

由于一般的共享存储并行机缺乏图形硬件,其上产生的3维科学计算数据,无法采用硬件加速的并行体绘制来就地进行数据可视化。为此基于本地并行机和分布式图形工作站,给出了一种混合并行绘制模型。该模型的工作原理是先将源数据存留在并行机,然后通过并行机的多处理器发布远程绘制命令流,进而通过操控工作站的图形硬件完成绘制;后期图像合成在并行机上执行,以发挥共享存储通信优势。通过负载平衡优化,并行绘制流水线有效实现了绘制、合成与显示的重叠。实验结果显示,该方法能以1024×1024图像分辨率,交互绘制并行机上的大规模数据场。     

Analogy and duality of texture analysis by harmonics or indicators

According to the classic harmonic approach, an orientation density function (odf)f is expanded into its corresponding Fourier orthogonal series with respect to generalized spherical harmonics, and a pole density function (pdf) into its corresponding Fourier orthogonal series with respect to spherical harmonics. While pdfs are even (antipodally symmetric) functions, odfs are generally not. Therefore, the part of the odf which cannot be determined from normal diffraction pdfs can be mathematically represented as the odd portion of its series expansion. If the odff is given, the even part can be mathematically represented explicitly in terms off itself. Thus, it is possible to render maps ofharmonic orientation ghosts, and to evaluatevariants of mathematical standard odfs resulting in identical pdfs independent of pdf data. However, if only normal diffraction pdfs are known, the data-dependentvariation width of feasible odfs remained unaccessible, and within the harmonic approach a measure of confidence in a solution of the pdf-to-odf inversion problem does not exist.According to any discrete approach, an odff defined on some setG of orientations is expanded into its corresponding Fourier orthogonal series with respect to indicator functions of the elements of a partition ofG, and a pdf defined on the upper (lower) unit hemisphereS ₊ ^{3 3} into its corresponding Fourier orthogonal series with respect to indicator functions of the elements of a partition ofS ₊ ³ . The ambiguity of the pdf-to-odf inversion problem is discussed in terms of column-rank deficiency of the augmented projection matrix. The implication of the harmonic approach to split an odf into auniquely determined and anundetermined part does no longer seem to be reasonable. However, it is possible to numerically determine data-dependent confidence intervals for the Fourier coefficients with respect to the indicator functions which can be immediately interpreted as mean orientation densities within the elements of the partition ofG. Doing so for all Fourier coefficients in the finite series expansion, i.e. for all elements of the partition of the setG, eventually results in the data-dependent variation width of odfs feasible with respect to given pdf data, and to the partitions ofG andS ₊ ³ .Thus it is confirmed that the appearance of orientation ghosts, in particular correlations oftrue andghost orientation components, depends on the representation of an odf. It may be questioned whether in practical applications the implicit assumption of the harmonic method that the even part can be determined uniquely and free of error is generally a reasonable initial condition to develop ghost correction procedures.     

Horizontal Voting Ensemble Based Predictive Modeling System for ColonCancer

Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture. Ten thousand (10000) microscopic images are taken to test the classification performance of the proposed PMS with the HVE method. The microscopic images obtained from the colon tissues are classified into ACA or benign by the proposed PMS. Results prove that the proposed PMS has ~8% performance improvement over the architecture without using the HVE method. The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2% of sensitivity and 99.4% of specificity. The overall accuracy of the proposed PMS is 99.3%, and without using the HVE method, it is only 91.3%.     

基于深度学习和灰度纹理特征的铁路接触网绝缘子状态检测

铁路接触网绝缘子状态检测对铁路行车安全有着 重大的意义,为解决目前人工对绝缘 子图像检测结果的不确定性,提出一种深度学习结合灰度纹理特征的检测方法。首先使用 Faster R-CNN (faster region-based convolutional neural network)目标检测算法对图像中绝缘子精确识别,再通过灰度共生矩阵对绝缘子纹理 特征进行分析提取,之后结合支持向量机将绝缘子分为正常绝缘子和异常绝缘子,实验数 据结果证明使用能量、熵、相关度3种纹理特征进行绝缘子状态分类时对实验数据中的正 常状态绝缘子的分类精度可达100%,异常状态绝缘子的分类精度达97.5%,最后依据绝缘 子图像灰度分布的周期性特点,利用灰度积分投影将异常绝缘子分为破损绝缘子和夹杂异 物绝缘子。实验结果表明所提方法可以有效对绝缘子状态进行检测分类。     

Performance comparison of texture feature analysis methods using PNN classifier for segmentation and classification of brain CT images

A computer software system is designed for the segmentation and classification of benign and malignant tumor slices in brain computed tomography images. In this paper, we present a texture analysis methods to find and select the texture features of the tumor region of each slice to be segmented by support vector machine (SVM). The images considered for this study belongs to 208 benign and malignant tumor slices. The features are extracted and selected using Student's t‐test. The reduced optimal features are used to model and train the probabilistic neural network (PNN) classifier and the classification accuracy is evaluated using k fold cross validation method. The segmentation results are also compared with the experienced radiologist ground truth. Quantitative analysis between ground truth and segmented tumor is presented in terms of quantitative measure of segmentation accuracy and the overlap similarity measure of Jaccard index. The proposed system provides some newly found texture features have important contribution in segmenting and classifying benign and malignant tumor slices efficiently and accurately. The experimental results show that the proposed hybrid texture feature analysis method using Probabilistic Neural Network (PNN) based classifier is able to achieve high segmentation and classification accuracy effectiveness as measured by Jaccard index, sensitivity, and specificity.     

集成电路用钽溅射靶材制备工艺研究

金属钽可作为集成电路中铜与硅基板的阻隔层材料,以防止铜与硅扩散生成铜硅合金影响电路性能。采用钽靶材通过物理气相沉积技术溅射钽到硅片上。靶材晶粒尺寸与织构取向影响溅射速率及溅射薄膜均匀性,要求钽靶材晶粒尺寸应小于100μm,在靶材整个厚度范围内应主要是(111)型织构。同时,为了避免薄膜存在杂质颗粒,要求钽靶材纯度不小于99.99%。本文对钽靶材电子束熔炼、锻造、轧制、热处理等关键工艺进行了系统研究,找到了一种有别于常规钽靶材生产工艺的新方法,所生产产品化学纯度、晶粒尺寸、织构等性能优良,产品成品率高,适于批量化生产。     

Rolling texture and its effect on tensile property of a near-α titanium alloy Ti60 plate

Rolling texture and its effect on tensile properties of Ti60 alloy plates were investigated in the present study. The plates wereβ-rolled at 1070℃ and(α+β)-rolled at 980℃, using uni-directionally rolling(UDR) and cross-directionally rolling(CDR) processes, respectively.β-rolled plates exhibited weak textures, which were attributed to the dispersive orientations of secondary α during the β→α phase transformation. Strong deformation textures formed in(α+β)-rolled plates as a result of slipping mechanisms: the strong T-type texture in UDR plate was related to {10 1 0}[11 2 0] slipping, while the B-type texture in CDR plate was relevant with {0001}[11 2 0] slip. Strong T-type textures led to anisotropic tensile properties. B-type textures would decrease such an anisotropy. The(α+β)-CDR process was found to be a candidate process for reducing anisotropy of Ti60 alloy plates.