FCM聚类算法在岩石图像分析中的应用

岩石的孔隙、喉道等特征是地质人员进行判断储层特征的重要参数.因岩石图像具有较高的复杂度,图像纹理相似,因而对岩石图像进行分析时有一定的难度.人工进行分析时,容易因为各种原因出现误差.本文提出利用模糊C均值算法(FCM)对鄂尔多斯盆地岩石铸体薄片进行聚类分析,实验结果能很好的将岩石铸体薄片中孔隙与岩石背景区分出来,为后期的岩石自动识别与分类奠定了基础.FCM是基于划分的一种非监督聚类算法.     

数字岩心渗流路径的特征研究

岩心的渗流特征决定了油气的分布规律和储藏信息,利用数字岩心技术建立孔隙网络模型,对真实岩心孔隙结构进行驱替模拟和渗流分析具有重要意义。然而孔隙结构的宏观渗流特性由其微观特征所决定,因此研究渗流路径特征具有重要意义。为了从微观层面来分析孔隙结构的渗流特性,研究了连通路径和渗流路径的搜索算法;给出渗流路径特征相关参数的定义和计算公式;最后给出孔隙网络模型的路径搜索结果,以及渗流路径特征参数结果。     

纳米CT技术在水驱后微观剩余油分布形态及量化分析中的应用

水驱、化学驱后微观剩余油赋存状态和分布规律是继续挖潜的基础。目前分析微观剩余油普遍采用密闭取心磨制薄片的方法,这样就破坏了多孔介质中流体的原始状态。为此,本文选用大庆油田葡12组1000 mD左右的天然岩心,进行室内驱替实验。采用纳米CT技术,在不破坏岩心内部结构且保持孔隙中流体原始赋存状态的前提下,扫描驱替后岩心孔隙中不同流体的分布状态,通过计算机三维重建技术还原出孔隙中水和不同类型剩余油的三维形貌,再现了乳状、簇状、粒间吸附状、孔隙表面薄膜状、颗粒吸附状剩余油的三维形态。并初步认识了不同化学驱替手段对各类微观剩余油的动用程度。     

基于U-net的铸体岩石薄片图像孔隙自动提取

使用岩石铸体薄片图像对岩石孔隙特征进行分析已经成为国内外石油地质部门常用方法之一,自动精确地分割铸体岩石薄片中的孔隙区域是定量计算孔隙参数的前提.目前传统RGB阈值分割方法精度不高,需要大量人工交互,而一些主流图像分割的深度学习网络泛化性能差,难以运用到实际中.针对这些问题,本文在U-net网络的基础上,提出了一种融合注意力机制和循环残差网络的模型.引入循环残差模块扩展网络深度,又融合了注意力机制模块,增加特征信息的学习权重.采用油田实验室常见的多种铸体薄片进行了实验,均取得了较好的分割结果,验证了本文方法的有效性和泛化性.     

基于K-means岩石铸体图像分割及孔隙度的计算

为了准确获取储层的孔隙度进行地层解释并建立地质模型,设计了基于k-means的岩石铸体图像分割及孔隙度的计算方法。本设计基于k-means聚类算法对彩色铸体薄片进行有效分割,并且在分割基础上结合形态学相关知识对图像进行更加精确识别,通过计算机判读二值图像中的孔隙面积与总图像面积比值得到孔隙度值。实验结果表明该方法可以取得好的聚类分割效果,并且使用其他检测方法和计算机判读2种方法求得的孔隙度基本一致,数值较吻合。     

计算扫描三维空间的岩石裂缝参数计算

本文讨论了一种岩心中裂缝自动识别的方法,通过计算机对CT扫描岩心得到的二维切片序列图进行三维重建,模拟出岩心在实际三维空间中的真实形态,利用普通孔隙,噪声和裂缝在三维形态特征上存在的重大差异,自动识别出该岩心中的裂缝,并计算出裂缝的相关参数。     

基于COM组件技术的岩心图像在线三维重建

在石油、地质部门,很多重要的地质参数都来自于钻井出来的岩心,而岩心图像是钻井得到岩心后的第一手资料,在对岩心的研究中发挥着重要作用.但只观看岩心表面图像不够直观,无法看到岩心的实际形状,因此需要进行三维重建.而在钻井过程中不可避免地造成岩心受到一些破坏.为此提出一种对岩心图像先进行简单修复,然后采用OpenGL技术,基...     

基于MATLAB的CT图像三维重建的研究与实现

介绍了利用MATLAB软件对CT切片图像进行三维重建的方法与程序实现。分别对体绘制法、面绘制法实现的三维重建进行了研究与讨论。利用MATLAB软件制作GUI界面,实现对肺部CT图像的三维重建以及切分操作。     

扫描电镜在砂岩孔隙铸钵上的应用

砂岩孔隙铸体是将地下含油水的岩石经洗油烘干，放到铸体仪中将树脂通过真空灌注，高温、高压固化，再酸化去除岩石颗粒，只保留孔隙骨架，表面再利用镀模机处理，利用扫描电镜进行观察和鉴定，获得砂岩孔隙特征的微观形貌信息。     

基于Beamlet的岩心裂缝提取算法

提出了一种基于多尺度Beamlet变换的岩心裂缝图像提取算法。首先，将采集到的灰度岩心裂缝图像，用大津阈值分割算法转换为二值图像，再利用Beamlet变换，通过选取不同的尺度和检验阀值，从二值图像中提取裂缝的线性特征，并根据像素统计出裂缝的相关分析数据。实验结果表明，此算法能在较复杂的岩心背景和噪声干扰情况下提取清晰的岩心裂缝，效果满意。     

基于视觉特性和小波分解的数字水印隐藏方法

本文提出了一种隐藏数字水印的新方法,该方法所隐藏的不是传统的序列码或比特流,而是将水印作为一幅二值图像来处理;并结合人眼视觉模型（ＨＶＳ）和图像的ＤＷＴ多尺度分解来隐藏水印。实验表明这种新方法在降低原始图像变换后视觉失真和提取的被隐藏水印图像失真两方面都达到较好的效果,鲁棒性也较好,这是一种很有发展前景的数字水印隐藏新方法。     

Segmentation of intrathoracic airway trees: a fuzzy logic approach

Three-dimensional (3-D) analysis of airway trees extracted from computed tomography (CT) image data can provide objective information about lung structure and function. However, manual analysis of 3-D lung CT images is tedious, time consuming and, thus, impractical for routine clinical care. The authors have previously reported an automated rule-based method for extraction of airway trees from 3-D CT images using a priori knowledge about airway-tree anatomy. Although the method's sensitivity was quite good, its specificity suffered from a large number of falsely detected airways. The authors present a new approach to airway-tree detection based on fuzzy logic that increases the method's specificity without compromising its sensitivity. The method was validated in 32 CT image slices randomly selected from five volumetric canine electron-beam CT data sets. The fuzzy-logic method significantly outperformed the previously reported rule-based method (p<0.002)     

Unsupervised image thresholding: hardware architecture and its usage for FPGA-SoC platform

ABSTRACT

Otsu’s global automatic image thresholding operation is used in various image processing applications. It needs computation of normalized cumulative histogram, mean and cumulative moments that are compute-intensive operations. In this paper, a custom architecture is presented for an efficient computation of Otsu’s algorithm along with its utilization as an intellectual property (IP) core in a field programmable gate array (FPGA) based system-on-chip (SoC) environment for the application of connected component analysis (CCA). A self-normalization technique is employed, where single-cycle, read–modify–write operations are performed with block random access memories (BRAMs) and digital signal processing (DSP)slices. The architecture is designed for 640 × 480 size of images that are captured by a high-resolution analouge camera and buffered in a DDR2 SDRAM of Xilinx ML-507 platform at 25.175 MHz clock frequency. The embedded PowerPC processor core is used to control the frame acquisition process. Experimental results on Virtex-5 xc5vfx70t FPGA device show that the architecture utilizes 1.4% slices, 2.7% BRAMs and 3.9% DSP48E slices. The total power consumption of the design is 1440.59 mW. The proposed architecture as an IP core is able to work in real-time with standard VGA resolution video and requires low computational resources.     

Multimodality Image Registration Using Spatial Procrustes Analysis and Modified Conditional Entropy

In this paper, we propose a new image registration technique using two kinds of information known as object shapes and voxel intensities. The proposed approach consists of two registration steps. First, an initial registration is carried out for two volume images by applying Procrustes analysis theory to the two sets of 3D feature points representing object shapes. During this first stage, a volume image is segmented by using a geometric deformable model. Then, 3D feature points are extracted from the boundary of a segmented object. We conduct an initial registration by applying Procrustes analysis theory with two sets of 3D feature points. Second, a fine registration is followed by using a new measure based on the entropy of conditional probabilities. Here, to achieve the final registration, we define a modified conditional entropy (MCE) computed from the joint histograms for voxel intensities of two given volume images. By using a two step registration method, we can improve the registration precision. To evaluate the performance of the proposed registration method, we conduct various experiments for our method as well as existing methods based on the mutual information (MI) and maximum likelihood (ML) criteria. We evaluate the precision of MI, ML and MCE-based measurements by comparing their registration traces obtained from magnetic resonance (MR) images and transformed computed tomography (CT) images with respect to x-translation and rotation. The experimental results show that our method has great potential for the registration of a variety of medical images.     

谷物害虫图像识别中特征值提取技术的研究

本文阐述了在仓储物害虫分类识别研究中利用计算机数字图像处理技术，对谷物害虫图像的一阶灰度值直方图和图像的目标区域，自动提4取静态仓储物害虫图像的数理统计特征、纹理特征和几何形状特征的主要技术和方法。试验结果表明，该方法可以为谷物害虫的计算机自动模式识别(快速分类)提供稳定的特征参数值，有效地提高了识别率。该方法为仓储物害虫的快速鉴定和分类研究开辟了新的途径。     

Hidden digital watermarks in images

An image authentication technique by embedding digital "watermarks" into images is proposed. Watermarking is a technique for labeling digital pictures by hiding secret information into the images. Sophisticated watermark embedding is a potential method to discourage unauthorized copying or attest the origin of the images. In our approach, we embed the watermarks with visually recognizable patterns into the images by selectively modifying the middle-frequency parts of the image. Several variations of the proposed method are addressed. The experimental results show that the proposed technique successfully survives image processing operations, image cropping, and the Joint Photographic Experts Group (JPEG) lossy compression.     

Statistical distributions of DCT coefficients and their application to an interframe compression algorithm for 3-D medical images

Displacement estimated interframe (DEI) coding, a coding scheme for 3-D medical image data sets such as X-ray computed tomography (CT) or magnetic resonance (MR) images, is presented. To take advantage of the correlation between contiguous slices, a displacement-compensated difference image based on the previous image is encoded. The best fitting distribution functions for the discrete cosine transform (DCT) coefficients obtained from displacement compensated difference images are determined and used in allocating bits and optimizing quantizers for the coefficients. The DEI scheme is compared with 2-D block discrete cosine transform (DCT) as well as a full-frame DCT using the bit allocation technique of S. Lo and H.K. Huang (1985). For X-ray CT head images, the present bit allocation and quantizer design, using an appropriate distribution model, resulted in a 13-dB improvement in the SNR compared to the full-frame DCT using the bit allocation technique. For an image set with 5-mm slice thickness, the DEI method gave about 5% improvement in the compression ratio on average and less blockiness at the same distortion. The performance gain increases to about 10% when the slice thickness decreases to 3 mm.     

基于计算全息技术的彩色CT真三维可视化

不同于现有的用计算机软件合成的CT 图像的伪 三维可视化,本文提出了一种基于计算全息技术的彩色CT 图像的真三维可视化技术。首先,利用计算全息技术对彩色CT图像进行三维重建,将一组 彩色CT图像的空间 二维信息融合成三维信息,并以计算全息图(CGH)的形式进行保存;然后,设计了彩色CT图 像光电再现与三维显示系 统,以液晶空间光调制器(LC-SLM)作为CGH的显示载体,通过计算机同时输入 3幅CGH,通过光电再现获得 三原色三维再现像,利用合色棱镜将三原色再现像合成为彩色图像,用雾屏作为彩色三维再 现像的显示载体,获 得彩色真三维CT图像。在全息图的计算过程中,基于CT图像的二维属性,采用了快速傅里 叶变换(FFT)算法,大大加快了计算速度。给出了理论分析与实验结果。     

Segmentation and analysis of the human airway tree from three-dimensional X-ray CT images

The lungs exchange air with the external environment via the pulmonary airways. Computed tomography (CT) scanning can be used to obtain detailed images of the pulmonary anatomy, including the airways. These images have been used to measure airway geometry, study airway reactivity, and guide surgical interventions. Prior to these applications, airway segmentation can be used to identify the airway lumen in the CT images. Airway tree segmentation can be performed manually by an image analyst, but the complexity of the tree makes manual segmentation tedious and extremely time-consuming. We describe a fully automatic technique for segmenting the airway tree in three-dimensional (3-D) CT images of the thorax. We use grayscale morphological reconstruction to identify candidate airways on CT slices and then reconstruct a connected 3-D airway tree. After segmentation, we estimate airway branchpoints based on connectivity changes in the reconstructed tree. Compared to manual analysis on 3-mm-thick electron-beam CT images, the automatic approach has an overall airway branch detection sensitivity of approximately 73%.     

Static Volumetric Three-Dimensional Display

We present here the development of a volumetric display based on the two-frequency, two-step upconversion technique using novel techniques for addressing the imaging volume. Two 1024 times 768 digital micromirror displays, driven by 30-W lasers at 1532 and 850 nm are utilized to generate fast scanning of the image volume in a 17 mm times 17 mm times 60 mm 2% erbium-doped lithium yttrium fluoride (YLF) crystal. Experimentally, images at 532 nm were created at 30 (frames) times 1024 times 768 resolution, resulting in almost 23 million voxels, at 500 frames/s, significantly higher than that obtained with three-dimensional (3D) raster scanning (frame is 2D cross-sectional plane of the 3D image). Imaging optics modified from projector systems and fiber-optically coupled to the source, combined with custom designed software for converting two-dimensional (2D) rendering of volumetric images into control signals for the digital micromirror displays allow single-color image generation with no flicker and natural depth cues. Improvements in optical power efficiency and the speed of digital micromirror display controller boards are needed for the system to reach its full potential. The resulting system has the potential to increase resolution to nearly 800 million voxels without viewpoint obstruction and expand to three-color imagery.