Complex-Valued Feature Masks by Directional Filtering of 3×3 Compass Feature Masks

: A two-dimensional (2D) N-directional edge detection filter was represented as a pair of real masks, i.e. by one complex-valued matrix [1]. The 3 × 3 compass gradient edge masks have often been used because of their simplicity, where N compass masks are constructed by rotating the kernel mask by an incremental angle of 2π/N. This paper presents complex-valued feature masks formulated by directional filtering of 3 × 3 feature masks (e.g. Prewitt, Sobel, Frei-Chen, Kirsch and roof masks), with the different number of directions N (= 8, 4 and 2). The same concept can be applied to any types of filtering/masks with arbitrary N. Received: 21 May 2001, Received in revised form: 15 November 2001, Accepted: 26 March 2002 ID="A1" Correspondence and offprint requests to: Professor Rae-Hong Park, Department of Electronic Engineering, Sogang University, C.P.O. Box 1142, Seoul 100–611, Korea. Email: rhpark@sogang.ac.kr     

一种改进型Canny边缘检测算法

边缘检测是提取图像特征的首要条件。文章提出了一种改进型Canny边缘检测算法。首先在边缘梯度计算时,将二维滤波模板分解为两个一维滤波模板,实现并行处理,提高运算速度;引入双阈值法则同时保证图像中强边缘点和弱边缘点的提取,并基于非局部最大值抑制原理检测边缘点,大大提高了边缘检测的精度和准确度;最后采用形态学算子实现对检测边缘进行细化处理,实现了单像素级细化边缘提取。实验结果表明,该算法在保证实时性的同时,具有很好的检测精度和准确度。     

Contour detection improved by frequency domain filtering of gradient image

We propose an intermediate computational step,frequency domain filtering of gradient image,to improve contour detection performance of gradient-based edge detectors.This step is inspired by analyzing the spectrum distribution of object contours and texture edges in the frequency domain of gradient image.We illustrate the principle and efect of this step by adding it to the Canny edge detector.The resulting operator can selectively retain object contours and region boundaries,and meanwhile can dramatically reduce non-meaningful elements caused by textured background.We use several types of images to compare the proposed method and other related methods qualitatively and quantitatively.Experimental results show that the proposed method can efectively enhance the contour detection of Canny edge detector and achieves similar detection performance to two other related methods but runs faster.     

Simultaneous unidirectional and bidirectional chaos-based optical communication using hybrid coupling semiconductor lasers

A simultaneous unidirectional and bidirectional chaos-based optical communication scheme based on a hybrid coupling semiconductor laser system that consists of one center semiconductor laser(CSL)and multiple side semiconductor lasers(SSLs)is proposed numerically.In this scheme,the SSLs oriented in a linear chain mutually couple with the adjacent SSLs and they are subjected to identical unidirectional injections from the CSL which is a chaotic external cavity semiconductor laser.We theoretically analyze the conditions for diferent types of chaos synchronization based on the symmetry operation mechanism and injection-locking mechanism,and numerically investigate the influences of operation parameters,parameter mismatch robustness,chaos pass filtering efects and communication performance of the hybrid coupling semiconductor laser system.The simulation results demonstrate that with proper selection of the unidirectional and mutual coupling conditions,the SSLs can synchronize with each other isochronally and simultaneously synchronize to the CSL completely or laggardly,which enables the proposed system to achieve a unidirectional broadcasting communication from the CSL to the SSLs and a bidirectional communication among the SSLs simultaneously.The proposed scheme is beneficial to the implementation of optical chaos communication networks.     

基于LOG和Canny算子的边缘检测算法

针对传统Canny算子抑制噪声和检测低强度边缘能力不足的问题,提出一种将LOG算子和Canny算子相结合的边缘检测方法。采用LOG算子对图像进行噪声过滤,从以下3个方面改进Canny算子实现边缘检测：(1)设计高斯滤波核对过滤掉噪声的图像进行边缘增强,使低强度边缘更容易被检测;(2)在M×N邻域中计算梯度幅值和方向;(3)将梯度方向结合梯度幅值计算,使梯度幅值在边缘检测中更具依据性。对增加椒盐噪声的图像进行实验,结果表明,该方法在最大程度抑制噪声的同时,能检测到更多的低强度边缘。     

On the location error of curved edges in low-pass filtered 2-D and3-D images

The authors study the location error of curved edges in two- and three-dimensional images after analog and digital low-pass filtering. The zero crossing of a second derivative filter is a well-known edge localization criterion. The second derivative in gradient direction (SDGD) produces a predictable bias in edge location towards the centers of curvature while the linear Laplace filter produces a shift in the opposite direction. Their sum called PLUS (PLUS=Laplace+SDGD) leads to an edge detector that finds curved edges one order more accurately than its constituents. This argument holds irrespective of the dimension. The influence of commonly used low-pass filters (such as the PSF originating from diffraction limited optics using incoherent light (2-D), the Gaussian filter with variable cutoff point (D-D), and the isotropic uniform filter (D-D)) is studied     

The Nonlinear Prefiltering and Difference of Estimates Approaches to Edge Detection: Applications of Stack Filters

The theory of stack filtering, which is a generalization of median filtering, is used in two different approaches to the detection of intensity edges in noisy images. The first approach is a generalization of median prefiltering: a stack filter or another median-type filter is used to smooth an image before a standard gradient estimator is applied. These prefiltering schemes retain the robustness of the median prefilter, but allow resolution of finer detail. The second approach, called the Difference of Estimates (DoE) approach, is a new formulation of a morphological scheme [Lee et al., IEEE Trans. Robotics Automat. RA-3, Apr. 1987, 142-156, Maragos and Ziff, IEEE Trans. Pattern Anal. Mach. Intell. 12(5), May 1990.] which has proven to be very sensitive to impulsive noise. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates yields the edge map. We find, for example, that this approach yields results comparable to those obtained with the Canny operator for images with additive Gaussian noise, but works much better when the noise is impulsive. In both approaches, the stack filters employed are trained to be optimal on images and noise that are "typical" examples of the target image. The robustness of stack filters leads to good performance for the target image, even when the statistics of the noise and/or image vary from those used in training. This is verified with extensive simulations.     

基于Canny算子的改进图像边缘检测算法

图像的边缘检测是图像处理领域内最关键的技术之一.针对工件分拣中需要机器视觉精确的检测出其边缘信息,并且从噪声和其他无关信息中筛选出来,提出了一种改进的Canny算法对工件进行边缘检测.该算法利用双边滤波来替代高斯滤波进行图像预处理,从而不仅可以保留更多的图像边缘细节也可以有效的去除噪声.而后运用最大类间方差法(Otsu...     

一种基于双边滤波的图像边缘检测方法

提出了一种基于双边滤波的图像边缘检测方法。利用图像像素的空间邻近度和灰度相似度的乘积来代替传统的Canny算法中高斯滤波的权系数,用该乘积与原图像进行卷积运算,然后通过非极大值抑制和高低阈值的方法检测出图像的边缘。基于双边滤波的图像边缘检测方法不仅有效地去除了图像中的噪声,而且很好地检测出了图像的真实边缘。     

基于多尺度自适应加权的改进Canny算子

在Canny算法框架下,对彩色遥感图像进行多尺度滤波分析。定义多个不同尺度的高斯滤波器,在每个尺度下,分别对遥感图像RGB三个通道进行滤波和梯度计算,取三个通道的梯度最大值为该尺度下的遥感图像梯度值。根据各个尺度的滤波器对噪声的抑制能力及边缘定位能力的不同,自适应地确定相应的权值大小,然后再将这些不同尺度下检测到的梯度图像用自适应确定的权值进行加权合成最终的梯度图像。在此基础上,由非极大值抑制和双阈值处理得到图像边缘。实验结果表明,该算法比传统的Canny算子在噪声抑制和边缘定位方面具有更优的性能,适合彩色遥感图像的边缘检测。     

可抗噪声的Canny改进边缘检测算法

由于图像噪声的存在,传统的边缘检测算法常常无法准确检测到边缘信息.本文分析了噪声条件下边缘信息的几何特征,提出一种基于几何边缘增强技术的边缘检测算法.首先采用Canny算子计算图像的初始边缘信息,然后根据初始边缘信息自动计算阈值排除弱边缘,对剩余边缘计算带方向梯度值进行增强,根据增强边缘信息自动计算双阈值,最后用双阈值方法检测、过滤并连接边缘.该算法提高了边缘检测的准确性,可以高效率地处理噪声和纹理导致的虚假边缘.     

基于改进Chamfer匹配的台标识别

已有电视台台标的识别技术多基于视频流处理,实时性较差,且对半透明台标识别效果不佳。为此,提出一种基于改进Chamfer匹配的台标识别方法。利用Canny算子提取台标边缘颜色及梯度方向,采用RANSAC算法对台标边缘进行优化,通过距离变换计算边缘梯度方向的距离图,并基于距离最短准则对其识别。实验结果表明,该方法能实现台标的单帧识别,克服半透明台标的识别难题,平均识别率达97.7%,平均识别时间为801 ms。     

A quadratic edge-finding filtering algorithm for cumulative resource constraints

The cumulative scheduling constraint, which enforces the sharing of a finite resource by several tasks, is widely used in constraint-based scheduling applications. Propagation of the cumulative constraint can be performed by several different filtering algorithms, often used in combination. One of the most important and successful of these filtering algorithms is edge-finding. Recent work by Vilím has resulted in a ?? (kn log n) algorithm for cumulative edge-finding (where n is the number of tasks and k is the number of distinct capacity requirements), as well as a new related filter, timetable edge-finding, with a complexity of ??(n ²). We present a sound ??(n ²) filtering algorithm for standard cumulative edge-finding, orthogonal to the work of Vilím; we also show how this algorithm’s filtering may be improved by incorporating some reasoning from extended edge-finding, with no increase in complexity. The complexity of the new algorithm does not strictly dominate previous edge-finders for small k, and it sometimes requires more iterations to reach the same fixpoint; nevertheless, results from Project Scheduling Problem Library benchmarks show that in practice this algorithm consistently outperforms earlier edge-finding filters, and remains competitive with timetable edge-finding, despite the latter algorithm’s generally stronger filtering.     

基于改进边缘检测的视觉注意计算模型

本文主要针对传统Itti视觉注意计算模型,引入边缘特征信息,优化视觉注意计算模型.在引入边缘特征信息的过程中,本文对Canny边缘检测算法进行改进：以改进后的双边滤波算法代替高斯滤波从而更好的保持边缘,借鉴Sobel算子从4个方向计算梯度幅值来代替原方法中的从2个方向来计算的过程,利用改进的OTSU算法选取双阈值代替手动设置阈值,从而降低图像分割时的误检、漏检现象.在实验中,我们发现,该方法相较于建立在普通Canny算法基础上的Itti视觉注意计算模型,对显著区域的提取效果上有很大的提高.     

基于改进Canny算子与图像形态学融合的边缘检测方法

传统Canny算法采用高斯滤波会造成图像的过度光滑,容易导致缓变边缘的丢失,而且梯度幅值的计算方法没有充分考虑到3x3邻域内周围像素对中心像素的影响.针对上述存在的问题与不足,结合小波融合技术的优势,提出了一种基于改进Canny算子与图像形态学融合的边缘检测方法,利用改进的Canny算子和图像形态学分别对图像进行边缘检测,然后应用小波融合技术把两种方法检测出来的边缘进行图像融合,得到最终的图像边缘.仿真结果表明,该算法具有较好的抗噪能力,有效地提高了边缘检测的准确性和完整性.     

一种自适应的Canny边缘检测算法*

针对传统的Canny算子进行边缘检测时易丢失边缘细节的缺陷,提出了一种改进的Canny边缘检测算法。该算法采用自适应的滤波器对图像进行滤波,在滤除图像噪声的同时保留了更多的图像边缘信息;根据图像的灰度均值与方差均值自动计算Canny算子的高低阈值。实验结果表明,该算法在检测到更多边缘细节的同时也具有很强的自适应性。     

Extended filters in bounded commutative Rl-monoids

The notion of extended filter of a filter associated to a subset of Rl-monoids is defined and related properties are investigated. Rachunek and Salounova proved that positive implicative filters and Boolean filters in Rl-monoids coincide with a condition in Rachunek and Salounova (Acta Univ Palacki Olomuc Fac rer nat Math 48(1):93–107, 2009). In this paper, we prove that positive implicative filters and Boolean filters coincide without any condition and get some results on various types of filters.     

基于递归滤波的边缘检测算法

针对包含不同程度噪声数字图像的边缘检测问题,提出了两种建立在房顶型模糊边缘模型基础上的平滑和边缘检测滤波器。首先用这些滤波算子以三阶递归的形式实现图像的平滑及梯度计算,再进行非极大值抑制及双阈值的边缘检测连接。实验结果表明,该方法得到的梯度图像均比Canny和Deriche滤波算子清晰,所得边缘图像也更加完整,检测时间也少于其他方法。     

自适应的线条画绘制

目的 基于参考图像的线条画生成是非真实感绘制最为常见的应用之一。尽可能模拟艺术家的创作风格生成疏密得当、具有层次感的线条画是这类工作的主要目标和挑战。本文提出一个自适应线画图绘制算法。方法 首先,将场景图像分割成若干个区域,分别计算每个区域亮度的方差以及每个像素到边界的最小距离,将每个区域的方差和面积的比值作为该区域的复杂度。然后,计算能反映其显著视觉特征的边缘切向流场。最后,使用基于流的各向异性高斯差分滤波生成线条画。在构造边缘切向流时,每个位置的切向量由其邻域的切向量加权而得到。文中增加了一个新的系数项,对于邻域的任意一个位置,如果它和参考位置在区域分类中属同一个类别。则该位置的权值更大。基于流的高斯差分自适应滤波过程中,高斯差分滤波的尺度参数和复杂度以及到区域边界距离有关。细节越丰富,离边界越近,尺度参数取值越小,这样得到的边缘比较细,同时可以防止将相邻小细线条连接成粗线条。然后,将高斯差分滤波结果沿着流线方向进行高斯滤波,对于细节丰富的区域,边缘比较多,尺度参数取值比较小,所连接边缘比较短,可以减少错误边缘可能。结果 对生物、树林、建筑、山河等具有代表性的图像,采用本文算法进行自动实时进行线条绘制,实验结果表明,采用本文算法所生成的线条随着区域场景的复杂程度呈现不同粗细和浓淡的变化,具有一定的层次感。因而本文算法能生成视觉特征鲜明、风格化效果突出的线条画,且能处理各种复杂场景的图像。结论 本文自适应参数的线条画生成算法,其算法参数调节以及算法效果优于固定参数的算法,本文算法在处理日常生活中各类主题场景的图像时均能取得良好效果。     

High dynamic range image tone mapping and retexturing using fast trilateral filtering

Using fast trilateral filtering we present a novel tone mapping and retexturing method for high dynamic range (HDR) images. Our new trilateral filtering-based tone mapping is about seven to ten times faster than that in [3]. Firstly, a novel tone mapping algorithm for HDR images is presented. It is based on fast bilateral filtering and two newly developed filters: the quasi-Cauchy function kernel filter and the fourth degree Taylor polynomial kernel filter. Secondly, a new gradient-based image retexturing method is introduced, which consists of three steps: 1) converting HDR images into low dynamic range (LDR) images using our fast trilateral filtering-based tone mapping method; 2) recovering the gradient luminance maps for the region to be retextured; 3) reconstructing the final retextured image by solving the Poisson equation. The proposed approach is suitable for HDR image tone mapping and retexturing, and experimental results have demonstrated the satisfactory performance of our method.