A novel feature-based tracking approach to the detection, localization, and 3-D reconstruction of internal defects in hardwood logs using computer tomography

A novel feature-based tracking approach based on the Kalman filter is proposed for the detection, localization, and 3-D reconstruction of internal defects in hardwood logs from cross-sectional computer tomography (CT) images. The defects are simultaneously detected, classified, localized, and reconstructed in 3-D space, making the proposed scheme computationally much more efficient than existing methods where the defects are detected and localized independently in individual CT image slices and the 3-D reconstruction of the defects accomplished via correspondence analysis across the various CT image slices. Robust techniques for defect detection and classification are proposed. Defect class-specific tracking schemes based on the Kalman filter, B-spline contour approximation, and Snakes contour fitting are designed which use the geometric parameters of the defect contours as the tracking variables. Experimental results on cross-sectional CT images of hardwood logs from select species such as white ash, hard maple, and red oak are presented.     

Multiresolution volume visualization with a texture-based octree

Although 3D texture-based volume rendering guarantees image quality almost interactively, it is difficult to maintain an interactive rate when the technique has to be exploited on large datasets. In this paper, we propose a new texture memory representation and a management policy that substitute the classical one-texel per voxel approach for a hierarchical approach. The hierarchical approach benefits nearly homogeneous regions and regions of lower interest. The proposed algorithm is based on a simple traversal of the octree representation of the volume data. Driven by a user-defined image quality, defined as a combination of data homogeneity and importance, a set of octree nodes (the cut) is selected to be rendered. The degree of accuracy applied for the representation of each one of the nodes of the cut in the texture memory is set independently according to the user-defined parameters. The variable resolution texture model obtained reduces the texture memory size and thus texture swapping, improving rendering speed.     

A sweeping algorithm for cluster hair rendering

projection-based sweeping algorithm , is developed to render hair images using the cluster model. Compared with a previous ray-tracing algorithm, the new algorithm offers several significant improvements: (1) it avoids the complex and expensive computation of the ray–cluster intersection; (2) it eliminates the time-consuming density-value evaluations at the sample points along a ray during ray tracing; (3) it allows more flexible variation of the density map along the trajectory to enhance the natural appearance of hair; and (4) it allows easier coarse/fine control over the density map for multi-resolution rendering. As a result, the new algorithm significantly improves rendering efficiency and hair image quality. Compared with the existing hardware-supported, texture-mapping projection methods, the new method allows more sophisticated shading models, accurate shadow calculation, and uniform handling of arbitrary slice orientations with accurate opacity accumulation. Published online: 22 May 2003     

基于小波的三维图像频域显示方法研究

提出了一种基于小波的频域体绘制算法(FWVR)进行三维图像重构。算法首先完成三维体数据的傅里叶变换和切平面提取,然后在频域中完成小波的多分辨率分解,并在不同分辨级上进行小波系数重建,最后做傅里叶逆变换,以得到观察平面上希望得到的体绘制图像。算法是基于CT成像和小波变换的原理,时间复杂度由视平面上的二维傅里叶逆变换决定,即O(N2logN)。应用此方法对128的医学体数据进行实验,结果证明该方法有效,采用伪彩色后的绘制效果3与光线投射法绘制效果基本相同,而速度大大提高。     

医学图像三维可视化中任意平面切片的研究与实现

对医学图像的三维重建技术进行研究,利用介于面绘制和体绘制之间的切片法来实现三维体数据可视化,并针对断层图像序列所生成三维体数据的切片方法进行了深入讨论。提出一种可操作性很强的切片方法,能较好地实现三维体数据中冠状面、矢状面、特别是任意平面的切片。同时,该方法已经用VC6．0结合VTK（Visualization Toolkit）编程进行实现,效果符合医学诊断要求,并得到了有关应用。     

Surface scratches: measuring, modeling and rendering

  One of the most important criticisms that can be made concerning synthesized images is the brand new and too clean aspect of objects. Surface color modifications can be used to introduce dirtiness or other aging-linked characteristics. Also, techniques such as bump or displacement mapping allow users to improve surface aspects by introducing geometrical perturbations. In parallel, the bidirectional reflectance distribution function (BRDF) is a crucial factor in achieving a high degree of realism. It turns out that surfaces are very often covered by defects such as scratches that are related to both textures and BRDFs due to their size. Scratches do not always affect the apparent geometry but nevertheless can remain strongly visible. None of the previously mentioned methods is suited for rendering these defects efficiently. We propose a new method, based on extensions to existing BRDFs and classical 2D texture mapping techniques, to render efficiently individually visible scratches. We use physical measurements on "real objects" to derive an accurate geometric model of scratches at small scale range (roughness scale), and we introduce a new geometric level between bump mapping and BRDFs. Beyond providing graphical results closely matching real cases, our method opens the way to a new class of considerations in computer graphics based on defects that require the coupling of both BRDFs and texturing techniques.     

Defect detection in textured surfaces using color ring-projection correlation

In this paper, we present a correlation scheme that incorporates a color ring-projection representation for the automatic inspection of defects in textured surfaces. The proposed color ring projection transforms a 2-D color image into a 1-D color pattern as a function of radius. For a search window of width W, data dimensionality is reduced from in the 2-D image to O(W) in the 1-D ring-projection space. The complexity of computing a correlation function is significantly reduced accordingly. Since the color ring-projection representation is invariant to rotation, the proposed method can be applied for both isotropic and oriented textures at arbitrary orientations. Experiments on regular textured surfaces have shown the efficacy of the proposed method. Received: 30 March 2000 / Accepted: 24 July 2001 Correspondence to: D.-M. Tsai (e-mail: iedmtsai@saturn.yzu.edu.tw)     

Texture-based volume rendering of adaptive mesh refinement data

Many phenomena in nature and engineering happen simultaneously on rather diverse spatial and temporal scales. In other words, they exhibit a multi-scale character. A special numerical multilevel technique associated with a particular hierarchical data structure is adaptive mesh refinement (AMR). This scheme achieves locally very high spatial and temporal resolutions. Due to its popularity, many scientists are in need of interactive visualization tools for AMR data. In this article, we present a 3D texture-based volume-rendering algorithm for AMR data that directly utilizes the hierarchical structure. Thereby fast rendering performance is achieved even for high-resolution data sets. To avoid multiple rendering of regions that are covered by grids of different levels of resolution, we propose a space partitioning scheme to decompose the volume into axis-aligned regions of equal-sized cells. Furthermore the problems of interpolation artifacts, opacity corrections, and texture memory limitations are addressed. Published online: November 6, 2002 Correspondence to: R. K?hler     

基于体绘制法的头部CT图像的三维重建

介绍了体绘制法重建医学三维图像的方法,基于真实CT图像数据,使用MATLAB的图像处理工具箱重建了头部的三维图像.     

采用特征跟踪的裂缝缺陷三维重建

通过对连续切片图像中裂缝区域跟踪实现裂缝缺陷的三维重建。分为以下三个步骤：区域预测、区域变形和表面绘制。预测是根据当前切片图像区域对下一个切片图像的区域进行预估。由于预测的结果和实际区域不一致采用区域变形技术得到实际的区域。对得到的区域进行表面绘制完成三维重建。在连续的切片图像中对提取出的区域不需对应关系的计算且在交互过程中利于特征的选取,因此计算成本低。实验结果表明通过上述方法可以对单个裂缝区域进行快速的跟踪和重建。     

NeTra: A toolbox for navigating large image databases

We present here an implementation of NeTra, a prototype image retrieval system that uses color, texture, shape and spatial location information in segmented image regions to search and retrieve similar regions from the database. A distinguishing aspect of this system is its incorporation of a robust automated image segmentation algorithm that allows object- or region-based search. Image segmentation significantly improves the quality of image retrieval when images contain multiple complex objects. Images are segmented into homogeneous regions at the time of ingest into the database, and image attributes that represent each of these regions are computed. In addition to image segmentation, other important components of the system include an efficient color representation, and indexing of color, texture, and shape features for fast search and retrieval. This representation allows the user to compose interesting queries such as “retrieve all images that contain regions that have the color of object A, texture of object B, shape of object C, and lie in the upper of the image”, where the individual objects could be regions belonging to different images. A Java-based web implementation of NeTra is available at http://vivaldi.ece.ucsb.edu/Netra.     

A transaction log analysis of a digital library

As experimental digital library testbeds gain wider acceptance and develop significant user bases, it becomes important to investigate the ways in which users interact with the systems in practice. Transaction logs are one source of usage information, and the information on user behavior can be culled from them both automatically (through calculation of summary statistics) and manually (by examining query strings for semantic clues on search motivations and searching strategy). We have conducted a transaction log analysis on user activity in the Computer Science Technical Reports Collection of the New Zealand Digital Library, and report insights gained and identify resulting search interface design issues. Specifically, we present the user demographics available with our library, discuss the use of operators and search options in queries, and examine patterns in query construction and refinement. We also describe common mistakes in searching, and examine the distribution of query terms appearing in the logs. Received: 17 December 1998/Revised: 25 May 1999     

Machine vision system for curved surface inspection

This application-oriented paper discusses a non-contact 3D range data measurement system to improve the performance of the existing 2D herring roe grading system. The existing system uses a single CCD camera with unstructured halogen lighting to acquire and analyze the shape of the 2D shape of the herring roe for size and deformity grading. Our system will act as an additional system module, which can be integrated into the existing 2D grading system, providing the additional third dimension to detect deformities in the herring roe, which were not detected in the 2D analysis. Furthermore, the additional surface depth data will increase the accuracy of the weight information used in the existing grading system. In the proposed system, multiple laser light stripes are projected into the herring roe and the single B/W CCD camera records the image of the scene. The distortion in the projected line pattern is due to the surface curvature and orientation. Utilizing the linear relation between the projected line distortion and surface depth, the range data was recovered from a single camera image. The measurement technique is described and the depth information is obtained through four steps: (1) image capture, (2) stripe extraction, (3) stripe coding, (4) triangulation, and system calibration. Then, this depth information can be converted into the curvature and orientation of the shape for deformity inspection, and also used for the weight estimation. Preliminary results are included to show the feasibility and performance of our measurement technique. The accuracy and reliability of the computerized herring roe grading system can be greatly improved by integrating this system into existing system in the future.     

Using vanishing points for camera calibration and coarse 3D reconstruction from a single image

In this paper, we show how to calibrate a camera and to recover the geometry and the photometry (textures) of objects from a single image. The aim of this work is to make it possible walkthrough and augment reality in a 3D model reconstructed from a single image. The calibration step does not need any calibration target and makes only four assumptions: (1) the single image contains at least two vanishing points, (2) the length (in 3D space) of one line segment (for determining the translation vector) in the image is known, (3) the principle point is the center of the image, and (4) the aspect ratio is fixed by the user. Each vanishing point is determined from a set of parallel lines. These vanishing points help determine a 3D world coordinate system R _o. After having computed the focal length, the rotation matrix and the translation vector are evaluated in turn for describing the rigid motion between R _o and the camera coordinate system R _c. Next, the reconstruction step consists in placing, rotating, scaling, and translating a rectangular 3D box that must fit at best with the potential objects within the scene as seen through the single image. With each face of a rectangular box, a texture that may contain holes due to invisible parts of certain objects is assigned. We show how the textures are extracted and how these holes are located and filled. Our method has been applied to various real images (pictures scanned from books, photographs) and synthetic images.     

ImageJ软件在三维立体CT图像处理中的应用

通过使用ImageJ这款开放源代码的图像处理软件对一组人头部颅内的CT切片进行处理,着重介绍了ImageJ在三维CT图像处理中的应用。给出了ImageJ进行三维CT图像处理主要的操作方法和处理后的效果图,为更好地使用ImageJ对CT图像进行三维处理提供参考。通过先计算各个感兴趣区域的面积,再累加实现了三维模型体积的计算。如果进一步知道图像的物理分辨率及CT切片的物理间距,则可以计算出感兴趣目标真实体积。     

计算机三维物体实体组建方法的研究

在计算机绘图和三维图像显示,例如激光扫描共焦显微图像、CT图像、MRI图像等的绘制和显示中,三维物体的组建是必不可少的。目前,三维物体的组建都是基于二维物体组建的基础之上。二维物体组建是基于连通性进行二维连通区域检出的,因而三维物体的组建速度比较慢。为此,文章提出一种新方法:围线积分法区域标号和链接表法三维叠片,用于三维图像中三维物体实体的组建。这种方法的基本原理是在三维二值图像中,先采用围线积分法区域标号,组建二维物体切片,再采用链接表法三维叠片,由二维物体切片组建三维实体。这种方法的优点是组建速度比较快。     

Spectral covariance and fuzzy regions for image indexing

To improve the discrimination power of color-indexing techniques, we encode a minimal amount of spatial information in the index. We tesselate each image with five partially overlapping, fuzzy regions. In the index, for each region in an image, we store its average color and the covariance matrix of the color distribution. A similiarity function of these color features is used to match query images with images in the database. In addition, we propose two measures to evaluate the performance of image-indexing techniques. We present experimental results using an image database which contains more than 11,600 color images.     

MODEEP: a motion-based object detection and pose estimation method for airborne FLIR sequences

In this paper, we present a method called MODEEP (Motion-based Object DEtection and Estimation of Pose) to detect independently moving objects (IMOs) in forward-looking infrared (FLIR) image sequences taken from an airborne, moving platform. Ego-motion effects are removed through a robust multi-scale affine image registration process. Thereafter, areas with residual motion indicate potential object activity. These areas are detected, refined and selected using a Bayesian classifier. The resulting regions are clustered into pairs such that each pair represents one object's front and rear end. Using motion and scene knowledge, we estimate object pose and establish a region of interest (ROI) for each pair. Edge elements within each ROI are used to segment the convex cover containing the IMO. We show detailed results on real, complex, cluttered and noisy sequences. Moreover, we outline the integration of our fast and robust system into a comprehensive automatic target recognition (ATR) and action classification system.