基于范例匹配的卡通形象设计方法研究

针对动画卡通形象的特点,选取典型卡通形象范例,并分割出范例图元形成图元库。利用傅里叶形状描述方法统一描绘用户输入草图和范例图元的轮廓特征,用输入草图的特征检索图元库,得到相似的范例图元,通过交互方式调整和修改图元,进而生成个性化的卡通形象。实验结果表明,该方法生成的卡通形象基本符合用户的设计意图。     

High-quality cardiac image dynamic visualization with feature enhancement and virtual surgical tool inclusion

Traditional approaches for rendering segmented volumetric data sets usually deliver unsatisfactory results, such as insufficient frame rate, low image quality, and intermixing artifacts. In this paper, we introduce a novel “color encoding” technique, based on graphics processing unit (GPU) accelerated raycasting and post-color attenuated classification, to address this problem. The result is an algorithm that can generate artifact-free dynamic volumetric images in real time. Next, we present a pre-integrated volume shading algorithm to reduce graphics memory requirements and computational cost when compared to traditional shading methods. We also present a normal-adjustment technique to improve image quality at clipped planes. Furthermore, we propose a new algorithm for color and depth texture indexing that permits virtual solid objects, such as surgical tools, to be manipulated within the dynamically rendered volumetric cardiac images in real time. Finally, all these techniques are combined within an environment that permits real-time visualization, enhancement, and manipulation of dynamic cardiac data sets.     

基于统计模式识别的岩石节理图像分割方法

岩石节理裂隙形状复杂,图像中含有很多噪声。而使用统计模式识别方法在分割图像时,可以首先使分类器学习图像中不同样本的特征,进而利用这些特征对图像中每个像素进行分类,实现分割。在设计统计模式识别的分类器时,我们提出使用基于核函数Fisher判别法构造分类器。使用该方法可以将图像高维的属性空间上的非线形判别转化为图像特征空间上的线形判别,而不需要知道从属性空间到特征空间的具体映射形式。通过对岩石节理裂隙图像分割实验表明,该方法能达到较其他方法更好的分割效果。     

Fusion of images interpreted by a new fuzzy classifier

This paper presents a global system for the fusion of images segmented by various methods and interpreted by a fuzzy classifier. A set of complementary segmentation operators is applied to the image. Each region of the segmented images is interpreted by the fuzzy classifier, through membership degrees to classes. The fuzzy classifier builds the classes automatically from examples, even in the case of complex data sets. Interpreted images are then merged by a fusion operator from the fuzzy set theory. Several fusion operators are compared. They trust more high membership degrees to classes, which are considered as reliability degrees. The fusion of the interpreted images improves the segmentation, and gives solutions to segmentation and interpretation evaluation.     

Real-time Biomechanically-based Muscle Volume Deformation using FEM

This paper presents a voxel-based biomechanical model for muscle deformation using finite element method (FEM) and volume graphics. Hierarchical voxel meshes are reconstructed from filtered segmented muscle images followed by FEM simulation and volume rendering. Physiological muscle force is considered and linear elastic muscle models for both static and dynamic cases are simulated by FEM. Voxel-based wireframe, polygon surface rendering, and volume rendering techniques are applied to show real-time muscle deformation processes as well as realistic animations.     

改进ICP算法用于多组图像的点云拼接与融合

随着计算机图形图像技术、机器视觉、虚拟现实技术等的发展,近年来,通过室外场景的序列图像进行三维重建的方法逐渐成为计算机视觉和图形学等相关领域的重点研究方向。但是,通常在图像的采集过程中由于受到测量设备和环境的影响,单次拍摄的序列组图可能并不能提取到足够的物体表面信息,导致不能够完成三维物体的重构,而不能为后续的目标识别和精确打击提供准确信息依据。针对此类问题,文中采用融合多组图像点云的方法,先利用彩色直方图匹配补充补拍图像序列,然后单独解算补拍组图的点云数据,再对不同点云的重叠部分利用改进的迭代最近点算法计算变换参数,最后进行融合处理,从而完成不同组图的点云数据间的配准和融合工作。实验证明,该方法能快速有效补充用于重构的点云数据,拼接和融合效果良好。     

基于LBC的计算机生成图像盲鉴别算法

针对现有的计算机生成图像盲鉴别算法选用的分类特征维度较高、通用性差等问题,提出了一种基于局部二进制计数模式的计算机生成图像盲鉴别算法.首先,将原始图像由RGB颜色空间转换为HSV颜色空间;然后,提取HSV颜色空间图像及其下采样图像的局部二进制计数模式矩阵,求取矩阵归一化直方图;最后,将上述直方图作为分类特征送入SVM分类器,实现计算机生成图像的盲鉴别.实验结果表明,该算法可以有效地鉴别自然图像和计算机生成图像,与现有算法相比具有更高的识别率和较低的特征维度.     

Discriminating between photorealistic computer graphics and natural images using fractal geometry

Rendering technology in computer graphics (CG) is now capable of producing highly photorealistic images,giving rise to the problem of how to identify CG images from natural images. Some methods were proposed to solve this problem. In this paper,we give a novel method from a new point of view of image perception. Although the photorealistic CG images are very similar to natural images,they are surrealistic and smoother than natural images,thus leading to the difference in perception. A part of features are derived from fractal dimension to capture the difference in color perception between CG images and natural images,and several generalized dimensions are used as the rest features to capture difference in coarseness. The effect of these features is verified by experiments. The average accuracy is over 91.2%.     

A probabilistic framework for component‐based vector graphics

We propose a framework for data‐driven manipulation and synthesis of component‐based vector graphics. Using labelled vector graphical images of a given type of object as input, our processing pipeline produces training data, learns a probabilistic Bayesian network from that training data, and offer various data‐driven vector‐related tools using synthesis functions. The tools ranges from data‐driven vector design to automatic synthesis of vector graphics. Our tools were well received by designers, our model provides good generalisation performance, also from small data sets, and our method for synthesis produces vector graphics deemed significantly more plausible compared with alternative methods.     

Text segmentation using gabor filters for automatic document processing

There is a considerable interest in designing automatic systems that will scan a given paper document and store it on electronic media for easier storage, manipulation, and access. Most documents contain graphics and images in addition to text. Thus, the document image has to be segmented to identify the text regions, so that OCR techniques may be applied only to those regions. In this paper, we present a simple method for document image segmentation in which text regions in a given document image are automatically identified. The proposed segmentation method for document images is based on a multichannel filtering approach to texture segmentation. The text in the document is considered as a textured region. Nontext contents in the document, such as blank spaces, graphics, and pictures, are considered as regions with different textures. Thus, the problem of segmenting document images into text and nontext regions can be posed as a texture segmentation problem. Two-dimensional Gabor filters are used to extract texture features for each of these regions. These filters have been extensively used earlier for a variety of texture segmentation tasks. Here we apply the same filters to the document image segmentation problem. Our segmentation method does not assume any a priori knowledge about the content or font styles of the document, and is shown to work even for skewed images and handwritten text. Results of the proposed segmentation method are presented for several test images which demonstrate the robustness of this technique. This work was supported by the National Science Foundation under NSF grant CDA-88-06599 and by a grant from E. 1. Du Pont De Nemours & Company.     

IStar: a raster representation for scalable image and volume data

Topology has been an important tool for analyzing scalar data and flow fields in visualization. In this work, we analyze the topology of multivariate image and volume data sets with discontinuities in order to create an efficient, raster-based representation we call IStar. Specifically, the topology information is used to create a dual structure that contains nodes and connectivity information for every segmentable region in the original data set. This graph structure, along with a sampled representation of the segmented data set, is embedded into a standard raster image which can then be substantially downsampled and compressed. During rendering, the raster image is upsampled and the dual graph is used to reconstruct the original function. Unlike traditional raster approaches, our representation can preserve sharp discontinuities at any level of magnification, much like scalable vector graphics. However, because our representation is raster-based, it is well suited to the real-time rendering pipeline. We demonstrate this by reconstructing our data sets on graphics hardware at real-time rates.     

Glioma grade classification using wavelet transform-local binary pattern based statistical texture features and geometric measures extracted from MRI

The objective of this study is to perform brain glioma grade classification by identifying an optimal quantitative feature set from conventional magnetic resonance images. In this work, a hybrid feature set comprising of statistical texture and geometric features is computed over entire segmented tumor volume. Discrete wavelet transform (DWT) and local binary pattern (LBP) techniques are combined to extract texture information from segmented tumour volume at multiple resolutions. Statistical texture features comprising of skewness, kurtosis and entropy are then computed from DWT-LBP transformed images. Geometric features are calculated from (i) fractal dimension (FD) of three dimensional (3D) volumes of tumour region, tumour border and tumour skeleton, and (ii) convexity parameters over complete segmented tumour volume. Statistical analysis revealed that extracted texture features are significantly different between high grade (HG) and low grade (LG) glioma patients (p < 0.05). FD-based geometric parameters are significantly higher for HG glioma patients in comparison to LG glioma patients. Our results reflect that HG glioma has more structural complexity than LG glioma. The optimised feature set comprising of DWT-LBP-based texture features and FD-based measures extracted from segmented tumour volume achieved 96% accuracy, 97% sensitivity and 95% specificity for glioma classification with Naive Bayes classifier.     

基于行为的恶意程序检测

提出了一个基于35维特征向量的恶意程序检测方法。特征向量的每一维用于表示一种恶意行为事件,每一事件由相应的Win32 API调用及其参数表示。实现了一个自动化行为追踪系统（Argus）用于行为特征的提取。实验数据集从8223个恶意可执行程序和2821个正常可执行程序中获取,并依据程序发生事件数的不同设立事件阈值,建立不同的训练集,分别用于训练贝叶斯分类器。实验表明,当事件阈值为3时,分类器达到最佳检测效果。     

基于运动信息与多尺度分水岭的视频目标分割

从视频序列中提取视频目标是基于内容编码中的一项关键技术。提出了将高阶统计运动检测和多尺度分水岭相结合的视频目标分割算法。该算法首先利用高阶统计运动检测算法检测出运动区域,通过后处理得到运动目标的初始模板。然后,用小波变换对视频图像进行多分辨率分解。在最低分辨率上应用分水岭算法分割得到具有精确边缘的分割区域,通过将区域融合后的区域逐步投影到高分辨率图像上并结合高分辨率图像上的分水岭算法逐步提取出具有精确边缘的区域。最后,将运动目标的初始模板和多尺度分水岭分割得到的区域结合起来提取出具有精确边缘的视频对象。实验结果表明该算法能有效地分割和提取出视频序列中的视频对象。     

多相期增强CT中肝内血管的自动分割

目的 在肝脏手术规划系统中,肝内精确的血管模型是实施肝脏分段和手术模拟的重要基础。为此提出一种基于多相期增强CT影像的肝内血管自动分割方法。方法 首先,采用各向异性滤波的方式减少图像上的噪声干扰。然后将图像灰度信息和汉森矩阵的特征值相结合,设计了一种新的滤波器,增强图像中的血管结构,以解决传统方法中血管连接处断裂的问题。最后,应用迭代式的自适应区域增长算法,进一步分割出增强图像中的血管。结果 使用5组临床上的真实数据测试算法的有效性,实验结果显示肝内血管由粗到细被完整分割出来。结论 本文肝脏CT血管分割方法,分别在不同尺度的增强图像对其进行处理,使得肝内血管从粗壮的主枝到细小的末端都能被很好地分割出来,能够获得正确的血管拓扑结构。     

一种基于相邻像素一致性的数码照片与计算机图形鉴别方法

愈来愈逼真的计算机图形正在颠覆人们"眼见为实"的传统观念,使人们难以分辨哪些是真实的数码照片,哪些是利用软件合成的图形.然而由于数码照片和计算机图形成像过程的不同,造成两类图像的相邻像素一致性存在较大差异.基于此认识,在HSV颜色空间提取了图像相邻像素一致性直方图特征和共生矩阵特征,对1300幅数码照片和500幅真实感计算机图形进行鉴别,识别率分别可达96%和93.9%.对视觉上难以区分的5幅数码照片和5幅计算机图形也取得了很好的识别效果.     

Parallel sphere rendering

Sphere rendering is an important method for visualizing molecular dynamics data. This paper presents a parallel algorithm that is almost 90 times faster than current graphics workstations. To render extremely large data sets and large images, the algorithm uses the MIMD features of the supercomputers to divide up the data, render independent partial images, and then finally composite the multiple partial images using an optimal method. The algorithm and performance results are presented for the CM-5 and the T3D.     

基于分形的水声图像目标探测

针对水声图像中人造物体的探测问题，给出了一种基于分形分析的方法，由于分形模型可以较好地模拟自然物体，而与人工物体存在较大差距，所以以其为主要特征可以准确地将人造物体从自然背景中探测出来。本文讨论了分维的提取方法，根据分形特征将水声图像标记为人造目标区域和非人造目标区域，并对一定噪声干扰下该方法的应用进行了研究，给出了相应的实验结果。实验结果表明，分形特征可以实现人造目标和自然物体的分类，并具有一定的抗噪声性，适宜对水声图像中的目标进行探测和识别。     

基于机器视觉的发动机包覆层表面缺陷检测技术

固体火箭发动机包覆层表面的缺陷检测是保证其使用安全性的重要手段.本文应用机器视觉技术实现发动机包覆层表面缺陷的自动检测.用工业相机采集发动机包覆层表面的图像,结合图像特点,通过多次实验分析,选择中值滤波方法进行滤波,采用图像模式匹配技术将缺陷从图像背景中分割出来,并将以上功能进行整合,设计缺陷自动检测系统.实验结果表明...