General sweep mathematical morphology

General sweep mathematical morphology provides a new class of morphological operations, which allow one to select varying shapes and orientations of structuring elements during the sweeping process. Such a class holds syntactic characteristics similar to algebraic morphology as well as sweep geometric modeling. The conventional morphology is a subclass of the general sweep morphology. The sweep morphological dilation/erosion provides a natural representation of sweep motion in the manufacturing processes, and the sweep opening/closing provides variant degrees of smoothing in image filtering. The theoretical framework for representation, computation and analysis of sweep morphology is presented in this paper. Its applications to the sweeping with deformations, image enhancement, edge linking, and shortest path planning for rotating objects are also discussed.     

A cellular logic array for image processing

A cellular logic image processor employing 192 cells in a 16 by 12 hexagonal array is described. The processor has been constructed and its performance assessed. The various classes of functions which can be implemented in the cellular array are discussed and sample programs explained in detail.     

基于数学形态学的SAR图像分割方法

图像分割是遥感图像处理中很重要的一步。因SAP图像通常带有较强的嗓声，用传统的边缘检测方法效果不理想。作者利用数学形态学开闭运算和混合滤波，可据目标的形状选用算法中的探针，取得了较好的滤波去噪和目标分割的效果。     

基于数学形态学的PET图像背景噪声处理算法*

基于数学形态学的背景噪声处理算法通过图像二值化、二值形态学处理及背景替换消除背景噪声.其减小了互信息配准测度的局部极值,改善了配准测度.     

基于模糊相似性的彩色形态学图像处理方法

为了将传统灰度图像数学形态学扩展到彩色图像,提出一种结合矢量空间模糊相似性的彩色形态学图像处理方法。首先,在RGB彩色空间中利用彩色矢量间的距离和角度定义模糊相似性测度,以刻画与人类视觉感知相一致的彩色相似程度;以上述相似性测度为准则定义彩色空间中任意一组彩色的上确界和下确界;利用中心像素及其结构单元内像素的上确界和下确界构建彩色形态学的基本操作,包括膨胀、腐蚀、开、闭等操作;进一步将提出的彩色形态学操作应用于高分辨率遥感图像,通过实验对比验证其对地物目标的形变和平滑能力,说明其实用性和有效性。     

A binary Hough transform and its efficient implementation in a systolic array architecture

This letter presents a binary Hough transform (BHT) derived from the conventional Hough transform with slope/ intercept parameterization and a systolic architecture for its efficient implementation using only adders and delay-elements.     

Mapping image processing operations onto a linear systolic machine

A high-performance systolic machine, called Warp, is operational at Carnegie Mellon. The machine has a programmable systolic array of linearly connected cells, each capable of performing 10 million floating-point operations per second. Many image processing operations have been programmed on the machine. This programming experience has yielded new insights in the mapping of image processing operations onto a parallel computer. This paper identifies three major mapping methods that are particularly suited to a Warp-like parallel machine using a linear array of processing elements. These mapping methods correspond to partitioning of input dataset, partitioning of output dataset, and partitioning of computation along the time domain (pipelining). Parallel implementations of several important image processing operations are presented to illustrate the mapping methods. These operations include the Fast Fourier transform (FFT), connected component labelling, Hough transform image warping and relaxation.H.T. Kungjoined the faculty of Carnegie Mellon University in 1974 after receiving his Ph.D. degree there. Appointed to Profesor in 1982, he is currently holding Shell Distinguished Chair in Computer Science at Carnegie Mellon. He was Guggenheim Fellow in 1983–84, and a full time Architecture Consultant to ESL, Inc., a subsidiary of TRW, in 1981. Dr. Kung's current research interests are in high-performance computer architectures and their applications. He has served on editorial boards of several journals and program committees of numerous conferences in VLSI and computer science.Jon A. Webbreceived the Ph.D. degree in computer science from The University of Texas at Austin in 1980. From 1981 he has worked on the faculty of the Department of Computer Science at Carnegie-Mellon University, where he is currently a Research Computer Scientist. His research interests include the theory of vision and parallel architectures for vision. He has published papers on the recovery of structure from motion, the shape of subjective contours, the design and use of a parallel architecture for low-level vision, and experiments in the visual control of a robot vehicle. Dr. Webb is a member of the IEEE Computer Society and the Association for Computing Machinery.The research was supported in part by Defense Advanced Research Projects Agency (DOD), monitored by the Air Force Avionics Laboratory under Contract F33615-84-K-1520, and Naval Electronic Systems Command under Contract N00039-85-C-0134, in part under ARPA Order number 5147, monitored by the US Army Engineer Topographic Laboratories under contract DACA 76-85-C-0002, and in part by the Office of Naval Research under Contracts N00014-80-C-0236, NR 048-659, and N00014-85-K-0152, NR SDRJ-007     

基于数学形态学的文档图像倾斜校正算法

随着信息采集技术的不断发展,文档图像在信息的数字化管理中越来越重要.对文档图像的倾斜校正进行了研究,给出了基于数学形态学和Hough变换相结合的算法,进行文档图像的倾斜校正,同时将算法应用于印刷体和手写体的文档图像.实验表明该算法可以有效应用于两种文档图像的倾斜校正.     

基于灰度形态学的红细胞图像边缘检测

边缘包含了图像很多重要的信息,边缘检测的好坏也直接决定了后续处理的效果。在利用数学形态学进行边缘检测后,会出现不需要的边缘,形成噪声。针对这种情况,提出一种计算中心像素与邻域像素均方差的方法对形态学边缘检测算子进行改进,该方法可以有效减少噪声,为以后对红细胞图像进行特征提取和分类打下良好的基础。     

Principles for implementing and optimizing mathematical image processing algorithms based on programmable logic

Typical approaches for implementing some mathematical algorithms based on programmable logic (reconfigurable logical integrated circuits) are proposed. Within the implementation of this approach, a hardware-software solution based on Xilinx FPGA of the Virtex family was designed and created that can be used to test the implemented algorithms and measure their performance for real problems. Two main specialized data processing modules are developed for practical testing. Along with the PCI-X computer interface and a parallel interface for different video devices, one of them was developed as an airborne computer on-board the satellite. The second module is designed for collecting, processing, and transferring large data flows (650 Mb/s) to PC via the external PCI-E ×4. Konstantin F. Lysakov. Born in 1982. Received his Bachelor degree from Novosibirsk State University in 2003. Received his Master degree from Novosibirsk State University in 2005. At present, he is a post-graduate student in Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Author of 12 publications in proceedings of international conferences. Mikhail Yu. Shadrin. Born in 1964. Received his Specialist degree from Novosibirsk State University in 1986. At present, he is a research engineer in Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Author of nine publications in proceedings of international conferences.     

基于形态学的自动浇注实时图像处理方法

分析实时浇注图像形态上的特性,提出一种基于二值图像形态学的浇注图像预处理方法.即先利用最佳阈值法.完成浇注图像的粗分割与初步去噪,然后利用图像区域连通标注算法,过滤图像中金属液液滴飞溅噪声,最后基于形态学中腐蚀、膨胀运算,选择合适结构元素对图像进行开运算,消除图像中金属液液柱干扰.该去噪方法可以提高浇口杯中金属液液位识别的准确性,能够为浇注自动控制提供良好的决策依据,符合应用要求现实可行.     

A reconfigurable computing framework for multi-scale cellular image processing

Cellular computing architectures represent an important class of computation that are characterized by simple processing elements, local interconnect and massive parallelism. These architectures are a good match for many image and video processing applications and can be substantially accelerated with Reconfigurable Computers. We present a flexible software/hardware framework for design, implementation and automatic synthesis of cellular image processing algorithms. The system provides an extremely flexible set of parallel, pipelined and time-multiplexed components which can be tailored through reconfigurable hardware for particular applications. The most novel aspects of our framework include a highly pipelined architecture for multi-scale cellular image processing as well as support for several different pattern recognition applications. In this paper, we will describe the system in detail and present our performance assessments. The system achieved speed-up of at least 100× for computationally expensive sub-problems and 10× for end-to-end applications compared to software implementations.     

鲁棒的形态学彩色图像边缘检测算法

针对传统边缘检测算子对噪声敏感的缺点,提出一种新的基于数学形态学的彩色图像边缘检测算法。该算法在传统形态学边缘检测算子的基础上,通过综合形态膨胀和形态腐蚀,设计出一种多尺度、多结构元素的抗噪型边缘检测算子,利用新算子对R、G、B三个分量分别检测出图像的边缘分量,对三个边缘分量进行融合得到最终的彩色边缘信息。仿真实验表明,该方法得到的边缘轮廓清晰,边缘定位精度较高,比传统的边缘检测方法具有更好的噪声鲁棒性和边缘细节保护能力。     

基于柔性形态学的梯度边缘检测算法

在深入研究柔性数学形态学边缘检测算法的基础上,提出比传统柔性形态学膨胀和腐蚀算子具有更强鲁棒性的柔性形态学膨胀和腐蚀算子,在此基础上提出柔性形态学梯度边缘检测算法,实验证明了该算法对噪声特别是脉冲噪声有很强的抑制作用,并能很好地检测出图像的边缘信息。     

General-purpose curvilinear object detection with fuzzy mathematical morphology

Curvilinear object detection is the common denominator of several applications. Some illustrative examples are road detection from aerial or satellite images, human airways from volumetric 3D scans or vascular structures in eye-fundus images. In this work, we propose two general-purpose curvilinear object detectors that may serve as building blocks for application-specific systems. To do so, we employ fuzzy mathematical morphology operators due to their robustness with respect to uncertainty and noise, and the trade-off they offer between expressive power and computational requirements. The extraction of linear features is based on, respectively, the fuzzy hit-or-miss transform and the fuzzy top-hat transform. They can be customized depending on the width of the objects of interest. We compare these two approaches with other state-of-the-art, general-purpose curvilinear object detectors to highlight their strengths and shortcomings. Both detectors succeed at localizing the objects of interest in different greyscale images.     

Analysis of a model for parallel image processing

An increasing awareness of the need for high speed parallel processing systems for image analysis has stimulated a great deal of interest in the design and development of such systems. Efficient processing schemes for several specific problems have been developed providing some insight into the general problems encountered in designing efficient image processing algorithms for parallel architectures. However it is still not clear what architecture or architectures are best suited for image processing in general, or how one may go about determining those which are. An approach that would allow application requirements to specify architectural features would be useful in this context. Working towards this goal, general principles are outlined for formulating parallel image processing tasks by exploiting parallelism in the algorithms and data structures employed. A synchronous parallel processing model is proposed which governs the communication and interaction between these tasks. This model presents a uniform framework for comparing and contrasting different formulation strategies. In addition, techniques are developed for analyzing instances of this model to determine a high level specification of a parallel architecture that best ‘matches’ the requirements of the corresponding application. It is also possible to derive initial estimates of the component capabilities that are required to achieve predefined performance levels. Such analysis tools are useful both in the design stage, in the selection of a specific parallel architecture, or in efficiently utilizing an existing one. In addition, the architecture independent specification of application requirements makes it a useful tool for benchmarking applications.     

A mathematical morphology approach to image based 3D particle shape analysis

Angularity is a critically important property in terms of the performance of natural particulate materials. It is also one of the most difficult to measure objectively using traditional methods. Here we present an innovative and efficient approach to the determination of particle angularity using image analysis. The direct use of three-dimensional data offers a more robust solution than the two-dimensional methods proposed previously. The algorithm is based on the application of mathematical morphological techniques to range imagery, and effectively simulates the natural wear processes by which rock particles become rounded. The analysis of simulated volume loss is used to provide a valuable measure of angularity that is geometrically commensurate with the traditional definitions. Experimental data obtained using real particle samples are presented and results correlated with existing methods in order to demonstrate the validity of the new approach. The implementation of technologies such as these has the potential to offer significant process optimisation and environmental benefits to the producers of aggregates and their composites. The technique is theoretically extendable to the quantification of surface texture.     

基于图像处理的焊管焊缝气孔检测

提出对x射线焊缝图像进行图像处理以判断焊缝质量,首先利用Sobel算子结合二值化过程以确定焊缝位置。在明确了焊缝位置后,通过实验发现气孔处图像的灰度值较焊缝的灰度值至少高出5,根据这一气孔的视觉效果,提出一种快速图像处理算法以检测焊缝内是否存在气孔。该算法通过计算焊缝内有无灰度值高出周围像素点灰度值至少5的区域来判断气孔,因此计算速度快,适合于现场实际应用。实际计算表明,所提算法可行、有效。     

A systolic array for the longest common subsequence problem

We introduce a linear systolic array for the Longest Common Subsequence (LCS, for short) problem. We first present an array of m identical cells which computes the length of an LCS of two strings of length m and n, respectively, in linear time (i.e., in time proportional to m + n). Then we show that, by extending any cell with the systolic stack introduced by Guibas and Liang (1982), a new array can be designed to recover an LCS in linear time.     

基于数学形态学和区域合并的医学CT图像分割*

针对传统分水岭算法分割腹部CT图像存在的过分割情况,提出了一种基于形态学优化和区域合并的分水岭分割算法。该方法先利用多尺度数学形态学方法检测出梯度图像,并用形态学重构去除细密纹理和噪声引起的局部极值,然后进行分水岭变换。为了产生有意义的分割,采用简单的区域灰度均值对变换后的图像进行有效的合并。实验结果表明,该方法能有效解决分水岭算法的过分割问题,得到较好的分割效果。