Fully deformable 3D digital partition model with topological control

We propose a purely discrete deformable partition model for segmenting 3D images. Its main ability is to maintain the topology of the partition during the minimization process. To do so, our main contribution is a new definition of multi-label simple points (ML simple point) that is easily computable. An ML simple point can be relabeled without modifying the overall topology of the partition. The definition is based on intervoxel properties, and uses the notion of collapse on cubical complexes. This work is an extension of a former restricted definition (Dupas et al., 2009) that prohibits the move of intersections of boundary surfaces. A deformation process is carried out with a greedy energy minimization algorithm. A discrete area estimator is used to approach at best standard regularizers classically used in continuous energy minimizing methods. We illustrate the potential of our approach with the segmentation of 3D medical images with known expected topology.     

Topological active volumes: A topology-adaptive deformable model for volume segmentation

This paper proposes a generic methodology for segmentation and reconstruction of volumetric datasets based on a deformable model, the topological active volumes (TAV). This model, based on a polyhedral mesh, integrates features of region-based and boundary-based segmentation methods in order to fit the contours of the objects and model its inner topology. Moreover, it implements automatic procedures, the so-called topological changes, that alter the mesh structure and allow the segmentation of complex features such as pronounced curvatures or holes, as well as the detection of several objects in the scene. This work presents the TAV model and the segmentation methodology and explains how the changes in the TAV structure can improve the adjustment process. In particular, it is focused on the increase of the mesh density in complex image areas in order to improve the adjustment to object surfaces. The suitability of the mesh structure and the segmentation methodology is analyzed and the accuracy of the proposed model is proved with both synthetic and real images.     

Robust algorithm for tunnel closing in 3D volumetric objects based on topological characteristics of points

In this letter, we propose a robust, linear in time modification of Aktouf, Bertrand and Perroton’s algorithm for tunnel (3D hole) closing in 3D volumetric objects. Our algorithm is insensitive to small distortions and branches. The algorithm has been tested on various 3D images including very complicated 3D crack propagation images. The results of the tests, discussion of the algorithm properties and future research plans are also included in the paper.     

An improved algorithm for gray image representation using non-symmetry and anti-packing model with triangles and rectangles

Although the triangle non-symmetry and anti-packing model (TNAM) representation for gray images is an effective image representation method, there is still much space left for optimization. In this paper, inspired by the optimization idea of the packing problem, we proposed an improved algorithm for gray image representation using the non-symmetry and anti-packing model with triangles and rectangles (NAMTR). By comparing the representation algorithm of the NAMTR with those of the TNAM and the popular linear quadtree, theoretical and experimental results presented in this paper show that the former can greatly reduce the number of sub-patterns or nodes and simultaneously save the data storage much more effectively than the latter, and therefore it is a better method to represent gray images. Representation method of the NAMTR, as envisaged in this paper, shows a very strong promise, and it is valuable for further theoretical research and potential business foreground, such as reducing storage space, increasing transmission speed and improving pattern match efficiency.     

一种快速有效实现三维实体重建的算法

从图的数组表示法这一基本表示方法,作为基点出发,将点、线、面、面环等信息用数组形式存储,从数组元素出发逐步实现了基于三视图的三维重建。实践表明,该方法充分利用数组形式的有序、对应、直接等特点,大大提高了三维重建的效率,减少了传统方法庞大的搜索空间和降低了时间复杂度。     

FPGA-based real-time 3D image preprocessing for image-guided medical interventions

Minimally invasive image-guided interventions (IGIs) are time and cost efficient, minimize unintended damage to healthy tissue, and lead to faster patient recovery. One emerging trend in IGI workflow is to use volumetric imaging modalities such as low-dose computed tomography (CT) and 3D ultrasound to provide real-time, accurate anatomical information intraoperatively. These intraoperative images, however, are often characterized by quantum (in low-dose CT) or speckle (in ultrasound) noise and must be enhanced prior to any advanced image processing. Anisotropic diffusion filtering and median filtering have been shown to be effective in enhancing and improving the visual quality of these images. However, achieving real-time performance, as required by IGIs, using software-only implementations is challenging because of the sheer size of the images and the arithmetic complexity of the filtering operations. We present a field-programmable gate array-based reconfigurable architecture for real-time preprocessing of intraoperative 3D images. The proposed architecture provides programmable kernels for 3D anisotropic diffusion filtering and 3D median filtering within the same framework. The implementation of this architecture using an Altera Stratix-II device achieved a voxel processing rate close to 200 MHz, which enables the use of these processing techniques in the IGI workflow prior to advanced operations such as segmentation, registration, and visualization.

结合图像分割和点云分割的障碍物检测算法

针对单目图像检测障碍物的低可靠性和当前双目视觉检测障碍物的局限性的问题,提出一种结合图像分割和点云分割技术的双目视觉障碍物检测方法。通过设定检测深度范围,分割障碍物点云与道路点云;采用将分割出的障碍物点云对应的视差图与图像分割得到的子图进行比较的策略,有效解决对不同深度、倾斜面和不规则障碍物检测效果差的问题。通过实验验证了在获得稀疏三维点云的情况下,该方法对障碍物的检测具有较好的鲁棒性。     

Pose-invariant face recognition using a 3D deformable model

The paper proposes a novel, pose-invariant face recognition system based on a deformable, generic 3D face model, that is a composite of: (1) an edge model, (2) a color region model and (3) a wireframe model for jointly describing the shape and important features of the face. The first two submodels are used for image analysis and the third mainly for face synthesis. In order to match the model to face images in arbitrary poses, the 3D model can be projected onto different 2D viewplanes based on rotation, translation and scale parameters, thereby generating multiple face-image templates (in different sizes and orientations). Face shape variations among people are taken into account by the deformation parameters of the model. Given an unknown face, its pose is estimated by model matching and the system synthesizes face images of known subjects in the same pose. The face is then classified as the subject whose synthesized image is most similar. The synthesized images are generated using a 3D face representation scheme which encodes the 3D shape and texture characteristics of the faces. This face representation is automatically derived from training face images of the subject. Experimental results show that the method is capable of determining pose and recognizing faces accurately over a wide range of poses and with naturally varying lighting conditions. Recognition rates of 92.3% have been achieved by the method with 10 training face images per person.     

基于Java 3D的医学图像三维重建系统

系统采用分层组件化的设计思想,在逻辑上分为三层:图像预处理层、图像分割层和用户界面层,实现了医学图像的二维标注与测量、三维体数据的分割、三维重建与交互功能。介绍了系统的体系结构和系统开发的主要技术方法。最后指出了系统的实用性和对医学研究方面的价值。     

3D scene retrieval and recognition with Depth Gradient Images

The intention of the strategy proposed in this paper is to solve the object retrieval problem in highly complex scenes using 3D information. In the worst case scenario the complexity of the scene includes several objects with irregular or free-form shapes, viewed from any direction, which are self-occluded or partially occluded by other objects with which they are in contact and whose appearance is uniform in intensity/color. This paper introduces and analyzes a new 3D recognition/pose strategy based on DGI (Depth Gradient Images) models. After comparing it with current representative techniques, we can affirm that DGI has very interesting prospects.The DGI representation synthesizes both surface and contour information, thus avoiding restrictions concerning the layout and visibility of the objects in the scene. This paper first explains the key concepts of the DGI representation and shows the main properties of this method in comparison to a set of known techniques. The performance of this strategy in real scenes is then reported. Details are also presented of a wide set of experimental tests, including results under occlusion, performance with injected noise and experiments with cluttered scenes of a high level of complexity.     

基于聚类分析的三维模型检索综述

为提高三维模型的检索性能,将聚类分析用于特征描述符的提取以及模型间相似性关系划分等方面,能够对三维模型进行较为合理的分类,对较大规模三维模型数据库的索引和组织进行完善,提高三维模型检索效率。针对当前主流的基于聚类的三维模型检索算法进行分析,比较几种聚类算法的优势与不足,在其基础上进行改进,并继续应用于三维模型的检索中。     

Correction of color information of a 3D model using a range intensity image

Most active optical range sensors record, simultaneously with the range image, the amount of light reflected at each measured surface location: this information forms what is called a range intensity image, also known as a reflectance image. This paper proposes a method that uses this type of image for the correction of the color information of a textured 3D model. This color information is usually obtained from color images acquired using a digital camera. The lighting condition for the color images are usually not controlled, thus this color information may not be accurate. On the other hand, the illumination condition for the range intensity image is known since it is obtained from a controlled lighting and observation configuration, as required for the purpose of active optical range measurement. The paper describes a method for combining the two sources of information, towards the goal of compensating for a reference range intensity image is first obtained by considering factors such as sensor properties, or distance and relative surface orientation of the measured surface. The color image of the corresponding surface portion is then corrected using this reference range intensity image. A B-spline interpolation technique is applied to reduce the noise of range intensity images. Finally, a method for the estimation of the illumination color is applied to compensate for the light source color. Experiments show the effectiveness of the correction method using range intensity images.     

A 2-point algorithm for 3D reconstruction of horizontal lines from a single omni-directional image

Reconstruction of 3D scenes with abundant straight line features has many applications in computer vision and robot navigation. Most approaches to this problem involve stereo techniques, in which a solution to the correspondence problem between at least two different images is required. In contrast, 3D reconstruction of straight horizontal lines from a single 2D omni-directional image is studied in this paper. The authors show that, for symmetric non-central catadioptric systems, a 3D horizontal line can be estimated using only two points extracted from a single image of the line. One of the two points is the symmetry point of the image curve of horizontal line, and the other is a generic point on the image curve. This paper improves on several prior works, including horizontal line detection in omni-directional image and line reconstruction from four viewing rays, but is simpler than those methods while being more robust. We evaluate how the precision of feature point extraction can affect line reconstruction accuracy, and discuss preliminary experimental results.     

2D clustering based discriminant analysis for 3D head model classification

This paper introduces a novel framework for 3D head model recognition based on the recently proposed 2D subspace analysis method. Two main contributions have been made. First, a 2D version of clustering-based discriminant analysis (CDA) is proposed, which combines the capability to model the multiple cluster structure embedded within a single class with the computational advantage that is characteristic of 2D subspace analysis methods. Second, we extend the applications of 2D subspace methods to the field of 3D head model classification by characterizing these models with 2D feature sets.     

电影2D/3D转换技术概述

3D电影能够比传统电影带来更好的视觉体验,并在近年来得到了快速的发展,但是片源不足成为制约这一产业兴起的主要瓶颈.在当前电影产业朝3D化方向蓬勃发展的趋势下,将2D电影转为3D电影是解决此问题的有效途径.文中对电影2D?3D转换技术进行了总结,按摄像机和场景相对运动的4种不同类型,介绍了其中几种基本的转换方法,并在此基础上进一步介绍了几种重要的高级转换方法,最后提出了今后的研究方向.     

A word extraction algorithm for machine-printed documents using a 3D neighborhood graph model

Automatic character recognition and image understanding of a given paper document are the main objectives of the computer vision field. For these problems, a basic step is to isolate characters and group words from these isolated characters. In this paper, we propose a new method for extracting characters from a mixed text/graphic machine-printed document and an algorithm for distinguishing words from the isolated characters. For extracting characters, we exploit several features (size, elongation, and density) of characters and propose a characteristic value for classification using the run-length frequency of the image component. In the context of word grouping, previous works have largely been concerned with words which are placed on a horizontal or vertical line. Our word grouping algorithm can group words which are on inclined lines, intersecting lines, and even curved lines. To do this, we introduce the 3D neighborhood graph model which is very useful and efficient for character classification and word grouping. In the 3D neighborhood graph model, each connected component of a text image segment is mapped onto 3D space according to the area of the bounding box and positional information from the document. We conducted tests with more than 20 English documents and more than ten oriental documents scanned from books, brochures, and magazines. Experimental results show that more than 95% of words are successfully extracted from general documents, even in very complicated oriental documents. Received August 3, 2001 / Accepted August 8, 2001     

三维无线传感器网络寿命和动态路由算法

无线传感器网络(WSNs)寿命受到电池能量的制约,利用无线能量传输技术对传感器节点进行充电,可以解决无线传感器网络的能量问题.以三维无线传感器网络为研究对象,证明三维最短Hamilton回路为无线充电设备遍历网络中节点的最优路径,提出了网络的连续时变模型,并简化复杂度为多项式的离散T+1阶段线性规划模型.仿真结果表明:通过运算离散T+1阶段线性规划模型能够使无线传感器网络持续运行.     

A universal texture segmentation and representation scheme based on ant colony optimization for iris image processing

This paper proposes a novel scheme for texture segmentation and representation based on Ant Colony Optimization (ACO). Texture segmentation and texture characteristic expression are two important areas in image pattern recognition. Nevertheless, until now, how to find an effective way for accomplishing these tasks is still a major challenge in practical applications such as iris image processing. We propose a framework for ACO based image processing methods. Considering the specific characteristics of various tasks, such a framework possesses the flexibility of only defining different criteria for ant behavior correspondingly. By defining different kinds of direction probability and movement difficulty for artificial ants, an ACO based image segmentation algorithm and a texture representation method are then presented for automatic iris image processing. Experimental results demonstrated that the ACO based image processing methods are competitive and quite promising, with excellent effectiveness and practicability especially for images with complex local texture situations.