Forward/Backward contour tracing with feedback

This correspondence describes a contour extraction algorithm which can gradually improve its results until the extracted contours are closed. This is achieved by an architecture with a feedback path for local smoothing. The feedback path is activated only when one or more contours obtained are not closed in order to initiate smoothing in noisy areas of the image to remove local irregularities that cause the problems. A forward/backward boundary tracing mechanism is employed to facilitate locating any troubled areas. A smoothing method appropriate for reducing local irregularities is discussed. The proposed algorithm is very suitable for those applications that demand closed contours, such as character recognition and blob detection.     

Minimal Surfaces Extend Shortest Path Segmentation Methods to 3D

Shortest paths have been used to segment object boundaries with both continuous and discrete image models. Although these techniques are well defined in 2D, the character of the path as an object boundary is not preserved in 3D. An object boundary in three dimensions is a 2D surface. However, many different extensions of the shortest path techniques to 3D have been previously proposed in which the 3D object is segmented via a collection of shortest paths rather than a minimal surface, leading to a solution which bears an uncertain relationship to the true minimal surface. Specifically, there is no guarantee that a minimal path between points on two closed contours will lie on the minimal surface joining these contours. We observe that an elegant solution to the computation of a minimal surface on a cellular complex (e.g., a 3D lattice) was given by Sullivan [47]. Sullivan showed that the discrete minimal surface connecting one or more closed contours may be found efficiently by solving a Minimum-cost Circulation Network Flow (MCNF) problem. In this work, we detail why a minimal surface properly extends a shortest path (in the context of a boundary) to three dimensions, present Sullivan's solution to this minimal surface problem via an MCNF calculation, and demonstrate the use of these minimal surfaces on the segmentation of image data.     

危险品运输中的最小风险最大流算法

在危险品运输中,为使风险降到最低,提出一种最小风险最大流算法。将所有可能影响风险的因素统一为一个风险值进行考虑,采用风险性比值的方法得到最小风险比值路线,并沿该路线进行增流,设计危险品运输中的最小风险算法。实例结果表明,与经典的求最小费用流的最小费用路线算法相比,该算法复杂性更低,占用空间更小。     

Interactive segmentation of non-star-shaped contours by dynamic programming

In this paper we present the Rack algorithm for the detection of optimal non-star-shaped contours in images. It is based on the combination of a user-driven image transformation and dynamic programming. The fundamental idea is to interactively specify and edit the general shape of the desired object by using a rack. This rack is used to model the image as a directed acyclic weighted graph that contains a path corresponding to the expected contour. In this graph, the shortest path with respect to an adequate cost function can be calculated efficiently via dynamic programming. The experimental results indicate the algorithm's ability of combining an acceptable amount of user interaction with generally good segmentation results.     

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

图像轮廓提取的迭代收缩算法

本文提出一种提取二值图轮廓的迭代收缩算法，在快速提取图像轮廓的同时，保持轮廓封闭性，并保留轮廓间关系信息，算法用于人脸识别系统中取得了较好的实验效果。     

Hybrid path planning method based on skeleton contour partitioning for robotic additive manufacturing

Establishing manufacturability design criteria for multidimensional complex parts can significantly reduce the production cost, shorten the manufacturing cycle, and improve the production quality of directed energy deposition. Therefore, there is an urgent need to establish a high-performance manufacturing design strategy for complex parts. Proposed here is a skeleton contour partitioning hybrid path-planning method that takes full advantage of the excellent geometric reducibility of the contour offset method and the outstanding flexibility of the zigzag path method, eliminating the influences of sharp corners and degradation on forming quality in the contour offset method. First, reference contours are obtained by subjecting the original contours to an inward–outward twice-offset process; incompletely filled regions are obtained by Boolean operations on the original and reference contours, and these regions are the ones to be optimized. Second, the optimized regions are merged into skeleton fill regions, and the fill paths are generated by a polygon trapezoidal partitioning recombination algorithm and an algorithm for generating optimal zigzag paths. Finally, the contour offset paths are split and regrouped based on the skeleton regions and are connected into a continuous forming path for each subregion, then all the forming paths are converted into robot printing tool paths from the skeleton-region filling paths to the contour-offset ones. The actual forming results for several parts with different geometric features are verified and compared with those of the traditional path-planning method, and it is concluded that the proposed method converges rapidly to the details of complex components and is highly feasible and applicable.     

一种求解最少时间最小费用路问题的算法

针对同时带有弧费用和弧时间的运输网络中最少时间最小费用路的问题,本文提出了一种算法。该算法能高效地求出此类网络中从源节点到目的节点的双目标最短路（最少时间最小费用路）。实例计算表明,该算法是有效的。     

Surface reconstruction by multiaxial triangulation

Outlines for reconstructing object surfaces are traditionally drawn from sequential images in parallel planes. The method presented here instead supports complex object topologies by drawing contours from multiaxial image planes. Multiaxial triangulation of an object in a given data volume involves four steps. First, the user generates contours interactively by selecting sample planes inside the data volume, then drawing object contours from the image corresponding to this sample plane. Our algorithm for multiaxial triangulation then processes these contours to verify consistency within and between sample planes. Second, it uses the sample planes containing the contours to partition the data volume into a divided volume. The contours are partitioned against the plane boundaries, and the contour parts (chains) are associated with faces, edges, and vertices in the divided volume. Third, these chains are joined into closed loops in the divided volume. Fourth, the loops are triangulated patchwise to create the surface model     

基于动态分块闭值去噪和改进的GDNI边缘连接的溢油遥感图像的边缘检测算法

海上溢油图像的边缘检测技术是最重要的海上溢油监测技术之一。无论是溢油的识别、位置的确定或者溢油量的获取,都需要首先确定溢油区域的边界信息。针对溢油图像的特点,提出了一种新颖的边缘检测算法。该算法由3部分组成:“非极大值抑制”实现了溢油图像的候选边缘检测;动态分块阂值算法实现了对噪声、伪边缘的清除,使获得的边缘更连续;改进的GDNI边缘连接算法实现了对去噪后图像中的中断边缘点的准确连接。通过实验结果证明,提出的算法能够得到清晰连续的溢油遥感图像的边界信息,较好地实现了具有低对比度、模糊边界以及噪声问题的溢油遥感图像的边缘检测,且具有很好的实时性。根据本算法得到的边缘检测信息,海上溢油能够更加容易和快速地被识别。     

基于视觉特征的多传感器图像配准

多传感器图像配准在空间图像处理中有非常重要的应用价值,但同时也面临着多源空间数据各异性困难。考虑到图像配准过程中的多分辨率视觉特征,采用基于小波的多分辨率图像分解来指导从粗到细的配准过程,利用扩展的轮廓跟踪算法提取满足视觉特征的轮廓,在轮廓链码曲率函数的基础上实现基于傅里叶变换的多分辨率形状特征匹配。与已有的基于特征的图像配准算法进行实验比较,实验结果表明该方法对于从多传感器得到的异质图像具有良好的配准效果。     

Segmentation of blurred objects by classification of isolabel contours

Segmentation of objects with blurred boundaries is an important and challenging problem, especially in the field of medical image analysis. A new approach to segmentation of homogeneous blurred objects in grayscale images is described in this paper. The proposed algorithm is based on building of an isolabel-contour map of the image and classification of closed isolabel contours by the SVM. Each closed isolabel contour is described by the feature vector that can include intensity-based features of the image area enclosed by the contour, as well as geometrical features of the contour shape. The image labeling procedure for construction of the training base becomes very fast and convenient because it is reduced to clicking on isolabel contours delineating the objects of interest on the isolabel-contour map. The proposed algorithm was applied to the problem of brain lesion segmentation in MRI and demonstrated performance figures above 98% on real data, both in sensitivity and in specificity.     

Fast template matching algorithm for contour images based on its chain coded description applied for human face identification

A new matching algorithm for contour images described by chain coded expression is presented. In our face authentication system, the isodensity contours has been introduced to differentiate between the facial features. These isodensity contours can be transformed into chain codes. By using these coded isodensity contours, remarkable improvement in the processing performance can be expected in terms of the processing time and memory requirements.From the computer simulation performed using images of 50 people, it turned out clear that the processing time was decreased to approximately one-seventh compared to the conventional method. With respect to memory requirement, it was reduced to a quarter.     

基于图像层级的机器素描研究

针对运用机械臂绘制的机器素描图像存在缺失真实感、艺术感,硬件设备复杂,难以普及的问题,提出基于图像层级的机器素描方法.该方法在运用灰度变换、滤波、二值化等图像预处理方法处理原始人物图像的基础上,分别提取出图像轮廓和图像内部填充区域两部分二值目标图像,通过简易路径规划遍历目标图像,根据遍历轨迹控制XY型简易机械臂绘制图像轮廓及按层级绘制模式填充图像内部区域,实现人物素描图像的绘制.实验结果表明,该系统可根据图像轮廓实现任意曲线的绘制,通过层级绘制模式包含环境因素达到了衬托素描图像使其更具层次感的目的.     

STL模型特征面片自适应分层算法*

为获得聚苯乙烯泡沫塑料(EPS)异步快速成形机所需的加工路径,提出了一种基于特征面片的Stereolithography(STL)模型自适应分层算法。算法根据模型在分层方向上的特征面片和最小加工厚度来确定分层位置和切割平面,无需坐标变换,可沿任意方向直接获取切片两端截面轮廓信息。该算法采用了一种新方法快速分割边界面片,通过轮廓信息整理可得到点轮廓、非闭合环轮廓、闭合环轮廓。闭合环轮廓经三角化后,可封闭切片端面。本文算法均采用Visual C++ 6.0实现,经实验证明运行稳定有效。     

一种新的粘连字符图像分割方法

针对监控画面采样图像中数字的自动识别问题,提出一种新的粘连字符图像分割方法。该方法以预处理后二值图像的连通状况来判定字符粘连的存在,并对粘连字符图像采用上下轮廓极值法确定候选粘连分割点,以双向最短路径确定合适的图像分割线路。仿真实验表明,该方法能有效解决粘连字符图像的分割问题。     

基于改进Live-Wire算法的无人机遥感影像标注

标签的制作是深度学习应用的关键步骤,为了克服无人机平台的复杂运动、光照条件不足、地物轮廓复杂等导致遥感影像的地物轮廓提取和标注的难点,文中提出一种改进的Live-wire算法并用于无人机遥感影像的典型地物的标签标注;通过改进模糊隶属度函数克服了Pal-King隶属函数灰度覆盖空间不足的缺陷并结合双阈值方法实现边缘点的提取,以改进的Pal-King的模糊边缘检测方法替代Live-Wire算法的拉普拉斯边缘提取方法;通过增加节点之间梯度幅值的变化特征优化代价函数,以提高Live-Wire算法的轮廓跟踪的连续性;大量的对比实验证明,相较于传统方法,改进的Live-Wire方法的轮廓提取和跟踪的稳健性、效率更高.     

Multiple Contour Finding and Perceptual Grouping using Minimal Paths

We address the problem of finding a set of contour curves in an image. We consider the problem of perceptual grouping and contour completion, where the data is a set of points in the image. A new method to find complete curves from a set of contours or edge points is presented. Our approach is based on a previous work on finding contours as minimal paths between two end points using the fast marching algorithm (L. D Cohen and R. Kimmel, International Journal of Computer Vision, Vol. 24, No. 1, pp. 57–78, 1997). Given a set of key points, we find the pairs of points that have to be linked and the paths that join them. We use the saddle points of the minimal action map. The paths are obtained by backpropagation from the saddle points to both points of each pair.In a second part, we propose a scheme that does not need key points for initialization. A set of key points is automatically selected from a larger set of admissible points. At the same time, saddle points between pairs of key points are extracted. Next, paths are drawn on the image and give the minimal paths between selected pairs of points. The set of minimal paths completes the initial set of contours and allows to close them. We illustrate the capability of our approach to close contours with examples on various images of sets of edge points of shapes with missing contours.     

Semi-Automated Extraction of Rivers from Digital Imagery

The manual production of vector maps from digital imagery can be a time consuming and costly process. Developing tools to automate this task for specific features, such as roads, has become an important research topic. The purpose of this paper was to present a technique for the semi-automatic extraction of multiple pixel width river features appearing in high resolution satellite imagery. This was accomplished using a two stage, multi-resolution procedure. Initial river extraction was performed on low resolution (SPOT multi-spectral, 20 m) imagery. The results from this low resolution extraction were then refined on higher resolution (KFA1000, panchromatic, 5 m) imagery to produce a detailed outline of the channel banks. To perform low resolution extraction a cost surface was generated to represent the combined local evidence of the presence of a river feature. The local evidence of a river was evaluated based on the results of a number of simple operators. Then, with user specified start and end points for the network, rivers were extracted by performing a least cost path search across this surface using the A* algorithm. The low resolution results were transferred to the high resolution imagery as closed contours which provided an estimate of the channel banks. These contours were then fit to the channel banks using the dynamic contours (or snakes) technique.     

Template-driven segmentation of confocal microscopy images

High quality 3D visualization of anatomic structures is necessary for many applications. The anatomic structures first need to be segmented. A variety of segmentation algorithms have been developed for this purpose. For confocal microscopy images, the noise introduced during the specimen preparation process, such as the procedure of penetration or staining, may cause images to be of low contrast in some regions. This property will make segmentation difficult. Also, the segmented structures may have rugged surfaces in 3D visualization. In this paper, we present a hybrid method that is suitable for segmentation of confocal microscopy images. A rough segmentation result is obtained from the atlas-based segmentation via affine registration. The boundaries of the segmentation result are close to the object boundaries, and are regarded as the initial contours of the active contour models. After convergence of the snake algorithm, the resulting contours in regions of low contrast are locally refined by parametric bicubic surfaces to alleviate the problem of incorrect convergence. The proposed method increases the accuracy of the snake algorithm because of better initial contours. Besides, it can provide smoother segmented results in 3D visualization.