一种基于圆内接直角三角形的圆检测方法

提出一种基于圆内接直角三角形的圆检测方法.创建基于有效像素位置的数组存储空间,将图像空间的搜索任务转移到压缩的数组空间中完成,配以特定的搜索算法,降低了该方法复杂度.在存储空间中分级别搜索直角三角形,将圆参量的求解转化为三角形参量的计算,避免了反复的平方、开方运算,减少了运算时间.在结果计算过程中,将单个直角三角形求解结果进行聚合,最终得到合理全局解.合成图以及实际图像的实验结果表明,该方法用于一般图像的圆检测时,具有独特的抑制噪声以及非圆上边缘点干扰的优势,实验快速、可靠,具有可重复性,检测精度小于1 pixel.     

A local voting and refinement method for circle detection

Improving the accuracy of circle detection in images is important for feature detection in remote sensing imagery. The standard Hough transform detects circles from the whole image space, which inclines to be disturbed by noise and the imperfection of the edge information. In this paper, a method of voting and determining circles locally is proposed. This method improves the accuracy and stability of circle detection in images with noise, incomplete edge information and complex backgrounds. Synthetic and real satellite images are used to demonstrate the effectivity of circle detection of the proposed method.     

稀疏孔径双圆周阵列的成像性能研究

针对传统稀疏孔径均匀圆周阵列的调制传递甬数在截止频率区域内易出现零值而影响成像质量的问题,提出一种由两个均匀圆周阵列嵌套构成的无冗余的双圆周稀疏孔径结构.给出该阵列的光瞳函数以及调制传递函数的解析表达式.以5-3结构的双圆周阵列为例,以实际空间截止频率为像质评价准则,从子孔径直径、内环圆周半径以及内环旋转角度等几个方面详细分析了双圆周阵列的成像特性,给出不同情况下的实际截止频率值,并对双圆周阵列稀疏孔径系统进行模拟成像和图像复原.将该结构与均匀圆周阵列.Comwell优化圆周阵列进行比较.结果表明,相同条件下,该阵列具有更大的实际空间截止频率,并且成像质量随着填充因子的减小而逐渐下降.     

同心圆检测中的区域划分算法

针对在基于图像的高准确度测量领域中同心圆图像检测这一实际问题,分析并实验验证了Hough变换法的缺点和一般圆拟合法的不足,根据系统光轴与同心圆旋转对称轴重合的特点,提出对图像平面进行区域划分再应用圆拟合法检测的方法.建立了基于距离空间聚类和基于随机采样两种区域划分算法,并且给出了圆心初值误差的极限.通过实验仿真,证明了新算法简单高效和可靠,而基于随机采样的算法更适合于实时检测的应用.     

基于特定感兴趣区采样的虹膜定位改进算法

从虹膜图像特点出发,以瞳孔形心为辅助点实现对虹膜图像特定感兴趣区采样.并且根据虹膜内外圆半径的生理特点设定Hough变换半径参量,依据虹膜内外圆近似同心圆来筛选与虹膜外圆最匹配的Hough变换结果.该算法在主动避开眼皮,睫毛干扰的同时又显著降低了Hough变换的计算量.通过对中科院自动化所CASIA虹膜数据库108组图像的虹膜定位测试结果表明,该方法平均定位时间0.83 s,定位准确率98.9%.     

A circle similarity algorithm for an automatic circular decomposition of blood cell images

This paper presents an iterative algorithm for circular decomposition which investigates the separation of overlapped circular particles of a binary image, in order to locate their center coordinates and to estimate their radii. Since this algorithm is based on the measure of a circle similarity of an object in an image to execute a search for concavities, object segmentation and circle recognition, its implementation is simpler than the algorithm based on polygonal approximation. In this work we compare the accuracy and robustness of the proposed circle similarity algorithm with a polygonal approximation based algorithm using synthetic images and real blood cell images. Both the algorithms are able to decompose connected blood cells. However, the input parameters of the polygonal approximation method shows high sensitivity to the shape or agglomeration of an object, while the proposed algorithm demonstrates more stable performance.     

一种改进的Sobel图像边缘检测算法

边缘检测在数字图像处理和计算机视觉中有着重要的应用。对数字图像处理中具有代表性的Sobel边缘检测算法进行了分析。针对该算法存在检测出的边缘粗且对噪声极其敏感的缺点,提出了一种改进算法。该算法对实际图像中出现的边缘类型进行了数学模型描述,然后把连续型的边缘模型作为研究对象,重新构造了对图像边缘方向进行检测的模板。针对Sobel边缘检测基于一阶导数极大值或二阶导数零交叉而带来的边缘定位准确度不高的缺点,对图像梯度图进行了细化处理。仿真结果表明:该算法对图像噪声干扰有较强的抑制能力,提取的边缘定位准确、结构细腻。     

Improvement in the Between-Class Variance Based on Lognormal Distribution for Accurate Image Segmentation

There are various distributions of image histograms where regions form symmetrically or asymmetrically based on the frequency of the intensity levels inside the image. In pure image processing, the process of optimal thresholding tends to accurately separate each region in the image histogram to obtain the segmented image. Otsu’s method is the most used technique in image segmentation. Otsu algorithm performs automatic image thresholding and returns the optimal threshold by maximizing between-class variance using the sum of Gaussian distribution for the intensity level in the histogram. There are various types of images where an intensity level has right-skewed histograms and does not fit with the between-class variance of the original Otsu algorithm. In this paper, we proposed an improvement of the between-class variance based on lognormal distribution, using the mean and the variance of the lognormal. The proposed model aims to handle the drawbacks of asymmetric distribution, especially for images with right-skewed intensity levels. Several images were tested for segmentation in the proposed model in parallel with the original Otsu method and the relevant work, including simulated images and Medical Resonance Imaging (MRI) of brain tumors. Two types of evaluation measures were used in this work based on unsupervised and supervised metrics. The proposed model showed superior results, and the segmented images indicated better threshold estimation against the original Otsu method and the related improvement.     

移动特征靶标的摄像机径向畸变标定

针对成像测量系统中镜头径向畸变影响测量精度的问题,提出了一种基于物面移动同心圆特征靶标的径向畸变标定方法。该方法先将固定在二维精密平台上的同心圆靶标置于垂直物面的特定位置,然后采集靶标图像,同时用最小二乘法以拟合得到的圆直径为条件,按一定方式移动特征靶标,直到拟合值达到极值或者在一定误差范围内。记录该幅图像,则其拟合得到的圆心坐标便是畸变中心,同时利用该幅图像,根据等差值半径和摄像机成像模型的半径的成像关系求出其畸变多项式系数。为提高特征靶标的移动效率,提出了坐标轮换最优化移动的方案。实验结果表明,该方法对畸变中心的标定精度可达0.6pixel,畸变多项式系数有效数字重复误差小于0.02,并可实现两者的一靶标定,且利用该法获得的参数能实现对畸变图像的准确校正。     

基于Shape Context和尺度不变特征变换的多模图像自动配准方法

提出了基于修正的尺度不变特征变换（SIFT）特征提取和Shape Context特征描述算子相结合的多模图像自动配准算法,该算法利用修正的SIFT算法提取多模图像中的特征点,然后采用Shape Context算子描述特征点,利用特征点周围区域边缘点的梯度方向形成特征向量。采用欧氏距离作为匹配标准对多模图像中特征点进行初始匹配,然后通过RANSAC算法消除误匹配的特征点对,并采用最小二乘法计算仿射变换参数,最后通过仿射变换和双线性插值实现图像配准。对红外图像和可见光图像的配准实验结果表明了本算法的有效性和稳定性。     

An algorithm for evaluating overlapping bubble images recorded by double pulsed laser holography

The present paper describes a method for evaluating images of a bubbly flow in stirred aerated tanks which are typical when pulsed laser holography is applied as the measuring technique. Features of the brightness histograms of reconstructed bubble images are discussed. A procedure is presented to evaluate the bubble images taken from a reconstructed hologram in order to determine the center of gravity of the bubble image. Double pulsed holograms were taken to measure bubble velocities and diameters simultaneously. In this case, overlapping bubble images are sometimes observed in the reconstruction. This significantly impedes the evaluation of the characteristics of the bubbles. Thus, an algorithm is presented in this work to distinguish between single and overlapping bubble images and to separate the overlapping bubble image in a two-dimensional image for a bubbly flow at low void fraction recorded from double pulse holograms. This algorithm was confirmed to be effective if the bubble images are extracted from the entire image.     

基于微分图像自相关的离焦模糊图像盲复原

针对离焦模糊图像的盲复原算法的研究具有重要的实际意义和实用价值.根据光学离焦成像模型,研究提出了一种基于微分图像自相关的离焦模糊图像超分辨力盲复原算法,即首先采用拉普拉斯算子对离焦模糊图像进行二阶微分并求微分图像的自相关,然后从自相关结果所包含的信息中确定离焦模糊半径,最后以离焦模糊模型结合MPMAP超分辨力复原算法对离焦模糊图像进行肓复原.实验证明:算法能够以较高的精度估计出离焦模糊半径并实现离焦模糊图像的盲复原,该算法较其它同类算法在减少计算过程中需要考虑的各类因素的同时也减少了计算量,提高了结果精度,依靠超分辨力复原算法获取更多的复原图像信息,已在实际刑侦和物证鉴定的离焦模糊图像判读和鉴定中获得成功应用.     

Efficient randomized Hough transform for circle detection using novel probability sampling and feature points

This paper presents an efficient randomized Hough transform algorithm for circle detection. It optimizes the methods for determining sample points and finding candidate circles. Due to these two optimizations, sampling validity is improved and many false circles are prevented from being regarded as candidate circles. Experimental results demonstrate that the proposed algorithm, which features a strong robustness and high resolution, can dramatically speed up circle detection as compared to other algorithms. It can also be applied to detect ellipses.     

Constraining the topology of the universe

The first year data from the Wilkinson Microwave Anisotropy Probe are used to place stringent constraints on the topology of the Universe. We search for pairs of circles on the sky with similar temperature patterns along each circle. We restrict the search to back-to-back circle pairs, and to nearly back-to-back circle pairs, as this covers the majority of the topologies that one might hope to detect in a nearly flat universe. We do not find any matched circles with radius greater than 25 degrees. For a wide class of models, the nondetection rules out the possibility that we live in a universe with topology scale smaller than 24 Gpc.     

基于CLAHE和开闭运算的绿色苹果图像分割

依据绿色苹果图像的自身特点,设计了一种分区域提取而后合并的图像分割方法。首先对图像进行限制对比度自适应直方图均衡化(contrast limited adaptive histogram equalization,CLAHE),增大果实和背景的颜色差,而后获取R-B色差图像,得到以光常区域为主的区域;然后用CLAHE处理后的图像进行开闭运算,提取局部极大值,得到以高亮区域为主的区域;最后将两区域合并获得完整的果实目标区域。为了验证该方法的有效性,运用Hough算法检测圆,并用相对偏差、圆心相对误差及半径相对误差三个评价指标来定量评价。试验结果表明,提取区域与果实目标区域相比,顺光下,相对偏差、圆心和半径相对误差平均值分别为3.59%,4.76%和2.60%;逆光下,三个指标的平均值分别为10.77%、16.77%、11.49%。无论是顺光还是逆光都有很好的识别效果,能满足机器人采摘果实的精确定位的要求。     

A distortion correction algorithm for fish-eye panoramic image of master-slave visual surveillance system

A master-slave visual surveillance system is composed of one fish-eye panoramic camera and one dynamic pan-tilt-zoom (PTZ) dome camera. In order to make PTZ dome camera zoom into all targets of interest in panoramic image, the fish-eye panoramic camera is fixed inclining towards the gravity direction, which may cause more obvious distortion. This paper proposed a novel method for the distortion correction of captured panoramic image based on the midpoint circle algorithm (MCA). The method uses incremental calculation of decision parameters to determine the pixel positions along a circle circumference, and both of the vertical and horizontal are rectilinearised. Experimental results show that our correction method based on MCA is efficient and effective. In particular, due to its low computational cost, our method can be applied on embedded camera platform without any extra hardware resources.     

一种快速检测圆的抗干扰变形模板方法

提出了一种新的参量式变形模板方法，用于检测带有缺陷和噪声的圆。根据圆的几何形状特性和梯度信息定义了模板的能量函数。然后通过动态调整模板的参量使能量函数和图像进行交互以把能量函数最大化。根据能量函数的定义，在其取得最大值时的参量即为所检测圆的位置参量。为了提高匹配运算速度，先求出被检测圆的圆心和半径的估计值，然后给出缩小了的搜索区域。在此搜索区域内采用贪婪优化的算法得到最终检测结果。实验结果表明算法可以在圆有较大缺陷和噪声的情况下，定位精度在1个像素以内，速度在0．5s左右；有很好的抗干扰和抗噪声能力，并有较快的运算速度。     

环形斑光束在非线性克尔介质中的自聚焦效应

通过数值求解非线性Schrödinger方程,详细讨论了环形斑光束在非线性克尔介质中的传输特性.当入射光超过一定的功率时,光束产生多级自聚焦现象,自聚焦焦点出现在离轴的环上;自聚焦阈值与环形光束的半径有关;传输过程中光斑存在横向分裂现象,并且分裂与聚焦交替进行;当两个半径不同的同轴环状光束同时在非线性介质中传输时产生耦合效应,耦合效应使其自聚焦增强.     

Image recovery from double amplitudes in fractional Fourier domain

The classical Gerchberg--Saxton algorithm is introduced into the image recovery in fractional Fourier domain after adaptation. When this algorithm is applied directly, its performance is good for smoothed image, but bad for unsmoothed image. Based on the diversity of fractional Fourier transform on its orders, this paper suggests a novel iterative algorithm, which extracts the information of the original image from amplitudes of its fractional Fourier transform at two orders. This new algorithm consists of two independent Gerchberg--Saxton procedures and an averaging operation in each circle. Numerical simulations are carried out to show its validity for both smoothed and unsmoothed images with most pairs of orders in the interval [0, 1].     

一种快速检测圆心的抗噪声亚像素算法

在印刷电路板的自动光学检测中，被检对象的空间对准是一个关键步骤，而传统的图像匹配技术由于其只能在像素级定位，而无法适应印刷电路板精确对准的要求。本文利用圆的几何对称性，提出一种在亚像素精度快速定位圆心的算法。