一种基于遗传算法的数字曲线多边形逼近方法

提出了一种基于遗传算法的数字曲线多边形改进逼近方法。该方法针对规则形状数字曲线的多边形逼近问题,以二进制向量序列表示的染色体作为每一个对应的逼近多边形候选解,将简化前后多边形质心偏移误差以及各被替换线段欧氏距离的方差引入到适应函数中,用迭代次数的sigmoid函数作为变异概率来控制遗传算法优化求解过程中的全局和局部搜索特性。实验结果表明,该方法对于保持曲线多边形简化逼近后的形状特征具有较好的效果。     

A fuzzy approach to digital image warping

Digital image warping addresses the problem of how to smoothly transform one digital image into another. The warping process has wide applications in computer animation and can be divided into two classes depending on the type of images being transformed. Gray image warping considers the transformation of one gray-scale image into another-a process also known as image metamorphosis. Binary image warping, on the other hand, addresses the transformation of binary images such as polygonal shapes. The focus in this article is on warping polygons. We can approach the warping of polygonal shapes in two steps. The first establishes a correspondence between the vertices of two given polygons. The second step interpolates the corresponding vertices to generate vertices of an intermediate polygon. This article presents new approaches to both steps. This new algorithm uses fuzzy techniques to warp polygons that have different locations, orientations, sizes and numbers of vertices. The algorithm is robust and extensible to curved shapes     

基于连接点的二维多角弧匹配

多角弧匹配问题的关键是，其既能反映多角弧的几何性质，又能反映多角弧拓扑结构的特征选取．在分析了多角弧几何形状的基础上，引入了连接点的概念，并用连接点集表示多角弧，这一表示在旋转和平移变换下是不变的。进一步取该连接点集作为匹配的特征集，给出了特征集之间匹配的算法．该算法是将连接点间的距离积分作为测量函数，使二维多角弧的匹配由连接点的匹配来决定．给出的模拟试验结果表明，该算法效果良好，并且对于数值污染具有健壮性。     

Visiting convex regions in a polygonal map

This paper is concerned with a variant of the multi-goal path planning in which goals are represented as convex polygons. The problem is to find a closed shortest path in a polygonal map such that all goals are visited. The proposed solution is based on a self-organizing map (SOM) algorithm for the traveling salesman problem. Neurons’ weights are considered as nodes inside the polygonal domain and connected nodes represent a path that evolves according to the proposed adaptation rules. In addition, a reference algorithm based on the solution of the traveling salesman problem and the consecutive touring polygons problem is provided to find high quality solutions of the created set of problems. The problems are designed to represent various inspection and patrolling tasks and can form a kind of benchmark set for multi-goal path planning algorithms. The performance of the algorithms is examined in this problem set, which includes an instance of the watchman route problem with restricted visibility range. The proposed SOM based algorithms provide a unified approach to solve various visibility based routing problems in polygonal maps while they provide a competitive quality of solutions to the reference algorithm with significantly lower computational requirements.     

Three-dimensional digital line segments

Digital arcs in 3-D digital pictures are defined. The digital image of an arc is also defined. A digital arc is defined to be a digital line segment if it is the digital image of a line segment. It is shown that a digital line segment may be characterized by the chord property holding for its projections onto the coordinate planes. It is also shown that a digital line segment may not be characterized by its own chord property. A linear time algorithm is presented that determines whether or not a digital arc is a digital line segment.     

Deep learning-empowered digital twin for visualized weld joint growth monitoring and penetration control

This paper presents an innovative digital twin to monitor and control complex manufacturing processes by integrating deep learning which offers strong feature extraction and analysis abilities. Taking welding manufacturing as a case study, a deep learning-empowered digital twin is developed as the visualized digital replica of the physical welding for joint growth monitoring and penetration control. In such a system, the information available directly from sensors including weld pool images, arc images, welding current and arc voltage is collected in pulsed gas tungsten arc welding (GTAW-P). Then, the undirect information charactering the weld joint geometry and determining the welding quality, including the weld joint top-side bead width (TSBW) and back-side bead width (BSBW), is computed/estimated by traditional image processing methods and deep convolutional neural networks (CNNs) respectively. Compared with single image source, weld pool image or arc image, the CNN model performs better when taking the 2-channel composite image combined by both as the input and the state-of-the-art accuracy in BSBW prediction with mean square error (MSE) as 0.047 mm² is obtained. Then, a decision-making strategy is developed to control the welding penetration to meet the quality requirement and applied successfully in various welding conditions. By modeling the weld joint cross section as an ellipse, the developed digital twin is visualized to offer a graphical user interface (GUI) for users perceiving the weld joint growth intuitively and effectively.     

Salient object detection using content-sensitive hypergraph representation and partitioning

As an important problem in image understanding, salient object detection is essential for image classification, object recognition, as well as image retrieval. In this paper, we propose a new approach to detect salient objects from an image by using content-sensitive hypergraph representation and partitioning. Firstly, a polygonal potential Region-Of-Interest (p-ROI) is extracted through analyzing the edge distribution in an image. Secondly, the image is represented by a content-sensitive hypergraph. Instead of using fixed features and parameters for all the images, we propose a new content-sensitive method for feature selection and hypergraph construction. In this method, the most discriminant color channel which maximizes the difference between p-ROI and the background is selected for each image. Also the number of neighbors in hyperedges is adjusted automatically according to the image content. Finally, an incremental hypergraph partitioning is utilized to generate the candidate regions for the final salient object detection, in which all the candidate regions are evaluated by p-ROI and the best match one will be the selected as final salient object. Our approach has been extensively evaluated on a large benchmark image database. Experimental results show that our approach can not only achieve considerable improvement in terms of commonly adopted performance measures in salient object detection, but also provide more precise object boundaries which is desirable for further image processing and understanding.     

Finding convex edge groupings in an image

In an image, there are groups of intensity edges that are likely to have resulted from the same convex object in a scene. A new method for identifying such groups is described here. Groups of edges that form a convex polygonal chain, such as a convex polygon or a spiral, are extracted from a set of image edge fragments. A key property of the method is that its output is no more complex than the original image. The method uses a triangulation of the linear edge segments in an image to define a local neighborhood that is scale invariant. From this local neighborhood a local convexity graph is constructed; this encodes which neighboring image edges could be part of a convex group. A path in the graph corresponds to a convex polygonal chain in the image, with a cyclic path corresponding to a polygon. We have implemented the method and found that it is efficient in practice as well as in theory. Examples are presented to illustrate that the technique finds intuitively salient groups, including for images of cluttered scenes.     

Fast computation of optimal polygonal approximations of digital planar closed curves

We face the problem of obtaining the optimal polygonal approximation of a digital planar curve. Given an ordered set of points on the Euclidean plane, an efficient method to obtain a polygonal approximation with the minimum number of segments, such that, the distortion error does not excess a threshold, is proposed. We present a novel algorithm to determine the optimal solution for the min-# polygonal approximation problem using the sum of square deviations criterion on closed curves.Our proposal, which is based on Mixed Integer Programming, has been tested using a set of contours of real images, obtaining significant differences in the computation time needed in comparison to the state-of-the-art methods.     

An efficient evolutionary algorithm for accurate polygonal approximation

An optimization problem for polygonal approximation of 2-D shapes is investigated in this paper. The optimization problem for a digital contour of N points with the approximating polygon of K vertices has a search space of C(N, K) instances, i.e., the number of ways of choosing K vertices out of N points. A genetic-algorithm-based method has been proposed for determining the optimal polygons of digital curves, and its performance is better than that of several existing methods for the polygonal approximation problems. This paper proposes an efficient evolutionary algorithm (EEA) with a novel orthogonal array crossover for obtaining the optimal solution to the polygonal approximation problem. It is shown empirically that the proposed EEA outperforms the existing genetic-algorithm-based method under the same cost conditions in terms of the quality of the best solution, average solution, variance of solutions, and the convergence speed, especially in solving large polygonal approximation problems.     

Exact Histogram Specification for Digital Images Using a Variational Approach

We consider the problem of exact histogram specification for digital (quantized) images. The goal is to transform the input digital image into an output (also digital) image that follows a prescribed histogram. Classical histogram modification methods are designed for real-valued images where all pixels have different values, so exact histogram specification is straightforward. Digital images typically have numerous pixels which share the same value. If one imposes the prescribed histogram to a digital image, usually there are numerous ways of assigning the prescribed values to the quantized values of the image. Therefore, exact histogram specification for digital images is an ill-posed problem. In order to guarantee that any prescribed histogram will be satisfied exactly, all pixels of the input digital image must be rearranged in a strictly ordered way. Further, the obtained strict ordering must faithfully account for the specific features of the input digital image. Such a task can be realized if we are able to extract additional representative information (called auxiliary attributes) from the input digital image. This is a real challenge in exact histogram specification for digital images. We propose a new method that efficiently provides a strict and faithful ordering for all pixel values. It is based on a well designed variational approach. Noticing that the input digital image contains quantization noise, we minimize a specialized objective function whose solution is a real-valued image with slightly reduced quantization noise, which remains very close to the input digital image. We show that all the pixels of this real-valued image can be ordered in a strict way with a very high probability. Then transforming the latter image into another digital image satisfying a specified histogram is an easy task. Numerical results show that our method outperforms by far the existing competing methods.     

基于连接点的3D多角弧匹配

为了满足实际应用的要求，快速地进行多角弧匹配是必要的，因此，提出了一种快速的3D多角弧表示和匹配的方法。该方法是在分析多角弧几何形状基础上，引入连接点的概念，同时，通过在连接点处建立局部直角坐标系来得到每一连接点处的球面坐标。并用连接点的球面坐标集表示多角弧，因这一表示在旋转和平移变换下是不变的，所以可取该球面坐标集作为多角弧匹配的特征集，用该特征集可保持多角弧的几何属性和拓扑结构。这样3D多角弧匹配就降为1D数值串匹配，从而使使匹配变得简单快速。其测量函数为对应连接点间的均方差。实验结果表明，该匹配算法效果良好，并且对于数值污染具有健壮性。     

Matching sets of 3D line segments with application to polygonal arcmatching

In this paper, we consider two sets of corresponding 3D line segments of equal length. We derive a closed-form solution for the coordinate transform (rotation and translation) that gives the best match between the two sets; best in the sense of a least-squares distance measure between the sets. We use these results as the basis to construct efficient algorithms for solving other problems in computer vision. Specifically, we address the problem of matching polygonal arcs, that is, the problem of finding a match between a short arc and a piece of long arc     

A generic and parallel algorithm for 2D digital curve polygonal approximation

In this paper, we present a generic topological and geometrical framework which allows to define and control several parallel algorithms for 2D digital curve approximation. The proposed technique is based on combinatorial map simplifications guided by geometrical criteria. We illustrate the genericity of the framework by defining three contour simplification methods: a polygonal approximation one based an area deviation computation; a digital straight segments reconstruction one which guaranties to obtain a loss-less representation; and a moment preserving simplification one which simplifies the contours while preserving geometrical moments of the image regions. Thanks to a complete experimental evaluation, we demonstrate that the proposed methods can be efficiently implemented in a multi-thread environment to simplify labeled image contours.     

An Investigation of Scalable SIMD I/O Techniques with Application to Parallel JPEG Compression

The problem inherent with any digital image or digital video system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is through the use of parallel processing. In this paper, we address the parallel implementation of the JPEG still-image compression standard on the MasPar MP-1, a massively parallel SIMD computer. We develop two novel byte alignment algorithms which are used to efficiently input and output compressed data from the parallel system, and present results which show real-time performance is possible. We also discuss several applications, such as motion JPEG, that can be used in multimedia systems.     

基于STM32的逆变弧焊电源控制器设计

数字化是弧焊电源的发展趋势,其关键在于控制器的数字化。目前市场上的大多数数字化产品价格相对高昂,采用STM32系列单片机进行经济型数字化弧焊电源控制器的设计和实现。该控制器采用数字式PI方法进行输出电流控制,并具有按键操作、液晶显示、过流保护、过热保护等功能。该控制器还具有良好的扩展I}生,可以通过修改程序增强系统功能。     

Determining Image Origin and Integrity Using Sensor Noise

In this paper, we provide a unified framework for identifying the source digital camera from its images and for revealing digitally altered images using photo-response nonuniformity noise (PRNU), which is a unique stochastic fingerprint of imaging sensors. The PRNU is obtained using a maximum-likelihood estimator derived from a simplified model of the sensor output. Both digital forensics tasks are then achieved by detecting the presence of sensor PRNU in specific regions of the image under investigation. The detection is formulated as a hypothesis testing problem. The statistical distribution of the optimal test statistics is obtained using a predictor of the test statistics on small image blocks. The predictor enables more accurate and meaningful estimation of probabilities of false rejection of a correct camera and missed detection of a tampered region. We also include a benchmark implementation of this framework and detailed experimental validation. The robustness of the proposed forensic methods is tested on common image processing, such as JPEG compression, gamma correction, resizing, and denoising.     

Polygonal space carving with geometric anti-aliasing

This paper proposes an algorithm that solves the shape recovery problem from N arbitrary images. By introducing a polygonal carving technique, the proposed algorithm can reconstruct the image-consistent polygonal shape that is patched by input images. This algorithm eliminates the invalid vertices and polygons from the initial polygonal grid space according to the color variance that represents their image consistency. The carved shape is refined by moving the outlier vertices on the boundary of each image. The final reconstructed shape faithfully accounts for the input images, and its textured appearance reflects the similar color property of the target object.     

A bivariate autoregressive technique for analysis andclassification of planar shapes

A bivariate autoregressive model is introduced for the analysis and classification of closed planar shapes. The boundary coordinate sequence of a digitized binary image is sampled to produce a polygonal approximation to an object's shape. This circular sample sequence is then represented by a vector autoregressive difference equation which models the individual Cartesian coordinate sequences as well as coordinate interdependencies. Several classification features which are functions or transformations of the estimated coefficient matrices and the associated residual error covariance matrices are developed. These features are shown to be invariant to object transformations such as translation, rotation, and scaling. Laboratory experiments involving object sets representative of industrial shapes are presented. Superior classification results are demonstrated     

TMS320C40实现电弧图像实时采集

提供了一种新型的电弧运动观测手段,利用高频CCD图像传感和DSP（TMS320C40）,设计出先进的电弧图像高速成像和RS－422A数据传输系统,将电弧光学图像认转化为便于计算机处理的数字化图像。以高速DS冢快速存储器为核心,设计并实现高速图像的数字缓冲接口系统,并采用DMA数据通信方式,以提高数据的传输速度,使采集系统主机能正确接收图像数字信号。利用该电弧图像采集系统对JQX－14FC型号的继电器进行了电弧图像采集。实验证明该系统具有较高的图像采集速度和图像分辨率,为更好地研究低压电器中电弧运动过程动态变化提供了新的分析方法和手段。