Generalized Perpendicular Bisector and exhaustive discrete circle recognition

This paper presents a generalization of the notion of circumcenter as the intersection of perpendicular bisectors. We define Generalized Perpendicular Bisectors between two regions as an area where each point is the center of at least one circle crossing both regions. This allows us to determine all the possible discrete circle centers that cross a given set of pixels. The possible radii can then easily be determined. This exhaustive digital circle parameter computation is adapted to various types of circles/digitization schemes such as Naïve, Pythagorean and standard/supercover circles.     

数字图像中基于多尺度几何分析的圆检测算法

特征检测是图像处理和模式识别中非常重要的问题,其检测效果直接影响模式识别和分类。基于多尺度几何分析（MGA）的思想,提出了一种圆检测方法―圆特征域上奇异点算法。该算法首先将圆特征曲线变换到圆特征域上,然后在圆特征域上进行小波分析以找出奇异点,奇异点坐标即为待检圆的坐标。该方法克服了Hough变换对灰度图像圆检测需要考虑灰度阈值或梯度的限制,可直接对二值图像或灰度图像进行检测。最后分析、比较了该算法与Hough算法的不同。     

Automatic circle detection on digital images with an adaptive bacterial foraging algorithm

This article presents an algorithm for the automatic detection of circular shapes from complicated and noisy images without using the conventional Hough transform methods. The proposed algorithm is based on a recently developed swarm intelligence technique, known as the bacterial foraging optimization (BFO). A new objective function has been derived to measure the resemblance of a candidate circle with an actual circle on the edge map of a given image based on the difference of their center locations and radii lengths. Guided by the values of this objective function (smaller means better), a set of encoded candidate circles are evolved using the BFO algorithm so that they can fit to the actual circles on the edge map of the image. The proposed method is able to detect single or multiple circles from a digital image through one shot of optimization. Simulation results over several synthetic as well as natural images with varying range of complexity validate the efficacy of the proposed technique in terms of its final accuracy, speed, and robustness.     

Circle Detection by Harmony Search Optimization

Automatic circle detection in digital images has received considerable attention over the last years in computer vision as several novel efforts aim for an optimal circle detector. This paper presents an algorithm for automatic detection of circular shapes considering the overall process as an optimization problem. The approach is based on the Harmony Search Algorithm (HSA), a derivative free meta-heuristic optimization algorithm inspired by musicians improvising new harmonies while playing. The algorithm uses the encoding of three points as candidate circles (harmonies) over the edge-only image. An objective function evaluates (harmony quality) if such candidate circles are actually present in the edge image. Guided by the values of this objective function, the set of encoded candidate circles are evolved using the HSA so that they can fit into the actual circles on the edge map of the image (optimal harmony). Experimental results from several tests on synthetic and natural images with a varying complexity range have been included to validate the efficiency of the proposed technique regarding accuracy, speed and robustness.     

Multi-circle detection on images using artificial bee colony (ABC) optimization

Hough transform has been the most common method for circle detection, exhibiting robustness, but adversely demanding considerable computational effort and large memory requirements. Alternative approaches include heuristic methods that employ iterative optimization procedures for detecting multiple circles. Since only one circle can be marked at each optimization cycle, multiple executions ought to be enforced in order to achieve multi-detection. This paper presents an algorithm for automatic detection of multiple circular shapes that considers the overall process as a multi-modal optimization problem. The approach is based on the artificial bee colony (ABC) algorithm, a swarm optimization algorithm inspired by the intelligent foraging behavior of honeybees. Unlike the original ABC algorithm, the proposed approach presents the addition of a memory for discarded solutions. Such memory allows holding important information regarding other local optima, which might have emerged during the optimization process. The detector uses a combination of three non-collinear edge points as parameters to determine circle candidates. A matching function (nectar-amount) determines if such circle candidates (bee-food sources) are actually present in the image. Guided by the values of such matching functions, the set of encoded candidate circles are evolved through the ABC algorithm so that the best candidate (global optimum) can be fitted into an actual circle within the edge-only image. Then, an analysis of the incorporated memory is executed in order to identify potential local optima, i.e., other circles. The proposed method is able to detect single or multiple circles from a digital image through only one optimization pass. Simulation results over several synthetic and natural images, with a varying range of complexity, validate the efficiency of the proposed technique regarding its accuracy, speed, and robustness.     

一种随机Hough变换检测圆的改进算法

从数字图像中检测出圆在计算机视觉中具有很重要的地位。随机H ough变换是检测圆的一种有效变换,但在处理复杂图像时,随机采样会引入大量的无效采样和积累。论文提出一种随机H ough变换检测圆的改进算法,算法的优点在于无需对候选圆之外的信息进行平方运算,只需进行简单的比较运算,有效地提高了检测速度。     

一种新的对随机Hough变换改进的检测圆的方法

从数字图像中检测出圆在计算机视觉中具有很重要的地位。随机Hough变换是检测圆的一种有效变换,但在处理复杂图像时,由于随机采样会引入大量的无效采样和积累。文章中提出一种在Teh-ChuanChenandKuo-LiangChung[4]的改进算法基础上,对随机Hough变换改进的检测圆的方法。     

Determining Digital Circularity Using Integer Intervals

Digital circularity is a well-researched topic for its real-world practicality to circularity measure, estimation of discrete curvature, circular arc segmentation, etc. The proposed work reveals a novel technique to determine whether a digital curve segment is digitally circular using the correspondence of its constituent runs with the square numbers in integer intervals. The notion of radii nesting is used to successively analyze these runs of digital points. Two algorithms have been proposed along with their demonstrations and detailed analysis, and a simple-yet-effective solution has been provided to expedite them using infimum circle and supremum circles that bound the initial range of radii. We have also shown how the proposed technique can be used for segmentation of an arbitrary digital curve segment into a sequence of circular arcs. Experimental results have been given to demonstrate the efficiency and elegance of the proposed technique.     

基于改进Hough变换的圆形物体检测

圆形(包括弧线)检测是数字图像处理过程中的经典问题之一,有着广泛的应用背景。基本的Hough变换方法是将图像中的每一边缘点映射到参数空间的一个区域,选取累积最多的参数。在现实生活中,由于噪音、数字化错误和图形变异等因素真实的图形经常被曲解,因此,图像在应用Hough变换后,很难找到单一的峰值,这也就造成了检测的难度。在Hough变换的原理基础上利用圆的几何特征提出了改进算法。理论和实验证明能获得较好的检测结果。     

基于微积分法的虹膜边缘检测技术的研究

当前社会,人们对于身份安全越来越重视,尤其是在一些高度保密或者涉及个人隐私方面的场合,一对一的身份识别显得尤为重要。而虹膜识别恰好具备高效、不易被仿造等特点,使其作为一项身份识别技术被推向了热潮。图像边缘检测一直是图像处理中的经典研究课题,也是至今仍没有得到圆满解决的一类问题。因此,探讨获取图像的边缘和轮廓的问题,是图像工程师们的重中之重。而虹膜识别技术中的边缘检测也如上所说是重要的一项技术,虹膜的内外边界可以近似地用圆来拟合。内圆表示虹膜与瞳孔的边界,外圆表示虹膜与巩膜的边界,但是这两个圆并不是同心圆。而如何更好、更准确地且不受外界干扰以及图像模糊情况下仍能较为有效地进行内外圆的边缘检测是研究的重点。文中就微积分法用于虹膜边缘检测方面展开了研究。     

An efficient contrast-enhancement method using the analog to digital converter

The study presents a hybrid method of contrast enhancement using the analog to digital converter (ADC) for use in high-speed industrial applications. The proposed framework processes the digitized image in efficient steps to generate the low and high offsets of the ADC. These offsets are used to modify the analog image signal by an affine transform, such that the digitization of the transformed signalis the enhanced image. Since the signal transformation is mostly done in the analog domain, the method is efficient, and its implementation is inexpensive. As an example, the enhancement method is used in applications where, given images of varying initial contrast, we can obtain an user-specified contrast for all images. These images are then segmented by a simpler image-processing algorithm. The method is a generalization of existing ADC-based enhancement methods and is compared experimentally to the digital domain techniques. An application of the method is given for the enhancement of laser-etched characters on industrial parts.     

Multi-circle detection on images inspired by collective animal behavior

Hough transform (HT) has been the most common method for circle detection that delivers robustness but adversely demands considerable computational efforts and large memory requirements. As an alternative to HT-based techniques, the problem of shape recognition has also been handled through optimization methods. In particular, extracting multiple circle primitives falls into the category of multi-modal optimization as each circle represents an optimum which must be detected within the feasible solution space. However, since all optimization-based circle detectors focus on finding only a single optimal solution, they need to be applied several times in order to extract all the primitives which results on time-consuming algorithms. This paper presents an algorithm for automatic detection of multiple circular shapes that considers the overall process as a multi-modal optimization problem. In the detection, the approach employs an evolutionary algorithm based on the way in which the animals behave collectively. In such an algorithm, searcher agents emulate a group of animals which interact to each other using simple biological rules. These rules are modeled as evolutionary operators. Such operators are applied to each agent considering that the complete group maintains a memory which stores the optimal solutions seen so-far by applying a competition principle. The detector uses a combination of three non-collinear edge points as parameters to determine circle candidates (possible solutions). A matching function determines if such circle candidates are actually present in the image. Guided by the values of such matching functions, the set of encoded candidate circles are evolved through the evolutionary algorithm so that the best candidate (global optimum) can be fitted into an actual circle within the edge-only image. Subsequently, an analysis of the incorporated memory is executed in order to identify potential local optima which represent other circles. Experimental results over several complex synthetic and natural images have validated the efficiency of the proposed technique regarding accuracy, speed and robustness.     

Application of Super High Definition Images in Telemedicine: System Requirements and Technologies for Teleradiology and Telepathology

It was recognized early on that the digitization of medical information would advance the efficiency of diagnostic technology. However, the digitization of image data, which makes up the majority of medical information, is dependent on advances in technologies such as input, processing, transmission, storage, and display. Insufficient advances in such technologies has effectively limited the digitization of image data for medical use. The result of this has been non-networked systems or LANs confined to a single hospital. Such isolated systems integrate only portions of digital medical images such as x-ray computer tomography (CT), magnetic resonance (MR), and computed radiography (CR).Fortunately, recent advances in the areas of super high definition image I/O, high-quality encoding, super high speed transmission, and high-capacity storage has turned the tide in favor of the digitization and networking of all medical information. This paper will focus on the digitization and networking of medical image information used within hospitals and provide a multifaceted study of the technologies necessary for these advances. This will allow us to discuss the present state of related technical developments and the level that has been attained so far. In addition, we have targeted image information that demands the highest level of quality (radiological and pathological images) for application in medical diagnosis using super high definition images, the image technology being developed by the authors of this paper. We will cover the concrete issues and approaches to solutions that must be investigated when building and networking a digital system.     

基于射影变换几何不变性的圆心像坐标的求取

在摄像机标定过程中,经常以圆（成像后为椭圆）作为标志,并以其中心——圆心作为标定点,圆心像坐标的求取是实现标定的关键所在。本文基于透视投影变换的理论,给出一种求圆心像坐标的方法,并对该方法的精度和稳定性给出一种验证模型,通过具体实验表明该方法具有较高的精度和稳定性。     

Apollonius tenth problem via radius adjustment and Möbius transformations

The Apollonius Tenth Problem, as defined by Apollonius of Perga circa 200 B.C., has been useful for various applications in addition to its theoretical interest. Even though particular cases have been handled previously, a general framework for the problem has never been reported. Presented in this paper is a theory to handle the Apollonius Tenth Problem by characterizing the spatial relationship among given circles and the desired Apollonius circles. Hence, the given three circles in this paper do not make any assumption regarding on the sizes of circles and the intersection/inclusion relationship among them. The observations made provide an easy-to-code algorithm to compute any desired Apollonius circle which is computationally efficient and robust.     

Generation of finite element mesh with variable size over an unbounded 2D domain

With the advance of the finite element, general fluid dynamic and traffic flow problems with arbitrary boundary definition over an unbounded domain are tackled. This paper describes an algorithm for the generation of finite element mesh of variable element size over an unbounded 2D domain by using the advancing front circle packing technique. Unlike the conventional frontal method, the procedure does not start from the object boundary but starts from a convenient point within an open domain. The sequence of construction of the packing circles is determined by the shortest distance from the fictitious centre in such a way that the generation front is more or less a circular loop with occasional minor concave parts due to element size variation. As soon as a circle is added to the generation front, finite elements are directly generated by properly connecting frontal segments with the centre of the new circle. In contrast to other mesh generation schemes, the domain boundary is not considered in the process of circle packing, this reduces a lot of geometrical checks for intersection with frontal segments, and a linear time complexity for mesh generation can be achieved. In case the boundary of the domain is needed, simply generate an unbounded mesh to cover the entire object. As the element adjacency relationship of the mesh has already been established in the circle packing process, insertion of boundary segments by neighbour tracing is fast and robust. Details of such a boundary recovery procedure are described, and practical meshing problems are given to demonstrate how physical objects are meshed by the unbounded meshing scheme followed by the insertion of domain boundaries.     

在数字印章中嵌入信息的方法及其实现

提出了一种在数字印章图像中的圆环上嵌入信息的方法,以实现文档认证的目的。分析了Bresenham圆序列的各种性质,提出了两个具体的圆环信息嵌入算法,分析了它们的嵌入量和平均形变量。第一个算法仅在圆环的外圆中嵌入数据,其形变较小;第二个算法同时在外圆和内圆中嵌入信息,使信息嵌入量增大了一倍。实验与分析表明,两种算法的平均形变量均小于1像素,其嵌入效果也令人满意。此外,两种算法在普通大小的数字印章中可分别嵌入HMAC-SHA512认证码和1 024比特的RSA签名结果。     

基于机器视觉的圆定位技术研究

针对视觉处理中常见的圆形目标检测,提出了结合Blob分析与最小二乘法圆拟合的定位检测方法,利用Blob分析算法实现粗定位,根据粗定位的输出检测目标圆的边界点,将其作为输入参数给最小二乘法圆拟合进行精定位;实现了在视场范围内对圆形区域自动检测及中心定位,在DSP视觉系统上以钢琴弦柱加工为检测背景对算法进行验证,实验结果表明算法满足工业应用中的实时性和精确性要求。     

Generation of triangular mesh with specified size by circle packing

This paper describes an algorithm for the generation of a finite element mesh with a specified element size over an unbound 2D domain using the advancing front circle packing technique. Unlike the conventional frontal method, the procedure does not start from the object boundary but starts from a convenient point within the open domain. As soon as a circle is added to the generation front, triangular elements are directly generated by properly connecting frontal segments with the centre of the new circle. Circles are packed closely and in contact with the existing circles by an iterative procedure according to the specified size control function. In contrast to other mesh generation schemes, the domain boundary is not considered in the process of circle packing, this reduces a lot of geometrical checks for intersection between frontal segments. If the mesh generation of a physical object is required, the object boundary can be introduced. The boundary recovery procedure is fast and robust by tracing neighbours of triangular elements. The finite element mesh generated by circle packing can also be used through a mapping process to produce parametric surface meshes of the required characteristics. The sizes of circles in the pack are controlled by the principal surface curvatures. Five examples are given to show the effectiveness and robustness of mesh generation and the application of circle packing to mesh generation over curved surfaces.     

快速随机Hough变换多圆检测算法

随机Hough变换是检测圆的一种有效方法,但在处理多圆复杂图像时随机采样带来的大量无效累积会导致计算量过大。文中提出一种基于随机Hough变换的快速多圆检测算法,除去三类噪声点,通过随机采样到的一点按照一定规则搜索另外两点来确定候选圆,用原始图像对候选圆进行证据积累以判断是否为真圆。理论分析和实验结果表明：该算法较其他算法能更快地检测出图像中的多个圆,具有较好的应用价值。