Preliminary experiments on technologies for satellite orbital maintenance using Micro-LabSat 1

For maturation of space activities, not only developing and using space systems is important, but also performing maintenance on them in their orbital environment is necessary in order to use them efficiently. The Communications Research Laboratory (CRL) has been studying an orbital maintenance system (OMS), specifically an on-orbit satellite maintenance system. An important first step is the capability to autonomously recognize and rendezvous with a target satellite. The CRL developed a microprocessor multi-chip module to control the OMS, including its robotic system and image processing, and installed it on Micro-LabSat for a mission called Micro-OLIVe (MicroLabSat was developed by NASDA and launched in 2002 together with the environment observation technology satellite ADEOS-II). In this paper, we describe the OMS concept, our experimental system and results of the Micro-OLIVe experiments. These experiments aimed at using the microprocessor multi-chip module to control the OMS, its camera units that use conventional C-MOS digital still cameras and its software used for flexible image processing.     

Space variant image processing

This paper describes a graph-based approach to image processing, intended for use with images obtained from sensors having space variant sampling grids. The connectivity graph (CG) is presented as a fundamental framework for posing image operations in any kind of space variant sensor. Partially motivated by the observation that human vision is strongly space variant, a number of research groups have been experimenting with space variant sensors. Such systems cover wide solid angles yet maintain high acuity in their central regions. Implementation of space variant systems pose at least two outstanding problems. First, such a system must be active, in order to utilize its high acuity region; second, there are significant image processing problems introduced by the non-uniform pixel size, shape and connectivity. Familiar image processing operations such as connected components, convolution, template matching, and even image translation, take on new and different forms when defined on space variant images. The present paper provides a general method for space variant image processing, based on a connectivity graph which represents the neighbor-relations in an arbitrarily structured sensor. We illustrate this approach with the following applications: (1) Connected components is reduced to its graph theoretic counterpart. We illustrate this on a logmap sensor, which possesses a difficult topology due to the branch cut associated with the complex logarithm function. (2) We show how to write local image operators in the connectivity graph that are independent of the sensor geometry. (3) We relate the connectivity graph to pyramids over irregular tessalations, and implement a local binarization operator in a 2-level pyramid. (4) Finally, we expand the connectivity graph into a structure we call a transformation graph, which represents the effects of geometric transformations in space variant image sensors. Using the transformation graph, we define an efficient algorithm for matching in the logmap images and solve the template matching problem for space variant images. Because of the very small number of pixels typical of logarithmic structured space variant arrays, the connectivity graph approach to image processing is suitable for real-time implementation, and provides a generic solution to a wide range of image processing applications with space variant sensors.This research was supported by DARPA/ONR #N00014-90-C-0049 and AFOSR Life Sciences #88-0275. Please address all correspondence to Richard S. Wallace, NYU Robotics Research Laboratory, 715 Broadway 12th Floor, New York, NY 10003. This report is copyright ©1993 by the authors. This report is a revised draft of a report published as New York University Courant Institute of Mathematical Sciences Computer Science Technical Report (No. 589 and Robotics Report No. 256), October, 1991. Last revised October.     

基于自组织动态神经网络的图像分割

图像分割是图像处理和模式识别的重要课题,而图像特征空间聚类是图像分割的一种重要方法,认为图像的特征是图像中待分割物体表面所特有而且恒定的特征,并将图像的特征映射到某种几何空间,称为特征空间,并且假定图像中不同的待分割物体在该特征空间中呈现为不同的聚集,提出了自组织动态网络(SODNN)聚类算法,并且利用该算法对图像特征空间聚类.该算法实现了神经网络结构的快速生长和动态调节,具有自动适应数据内在分布特征和聚类结果更为准确稳定的特点.利用SODNN算法对图像颜色空间进行聚类的同时综合了图像的位置信息来实现图像分割.实验表明分割结果与人工分割结果具有较好的一致性.     

Antiforgery: a novel pseudo-outer product based fuzzy neural network driven signature verification system

A novel pseudo-outer product based fuzzy neural network (POPFNN-TVR) driven signature verification system called the antiforgery system is presented in this paper. As Plamondon and Lorette have stated that the design of a signature verification system generally requires the solution of five types of problems: data acquisition, preprocessing, feature extraction, comparison process, and performance evaluation. However, unlike most existing automatic signature verification systems which employ traditional techniques (i.e. image processing techniques) to solve these problems, the proposed system is constructed on the basis of a novel fuzzy neural network called the POPFNN-TVR. The characteristics of POPFNN-TVR, such as the learning ability, generalization ability, and high computational ability, make antiforgery particularly powerful when verifying skilled forgeries. To demonstrate the efficacy of POPFNN-TVR and its application in the antiforgery system, several types of experiments have been designed and implemented in this work. The experimental results and analysis are presented at the end of the paper for discussion.     

一种基于投影算子的二值图像处理算法

二值图像的处理是图像内容分析领域的一个关键环节,处理效果严重影响图像分析的结果.以历史文档为处理对象,提出了基于投影的二值图像处理算法,通过对投影数组的处理实现灰度图像二值化阈值的合理选取、文档外边框的自动检测和图像污点的自动检测.实践证明该算法处理效果好,时间复杂度和空间复杂度低,是一种切实可行的好方法.     

MIPAS: A neural network-based multimedia information processing and analysis system

This paper presents the structure and design criteria of a neural network-based multimedia information processing and analysis system (MIPAS) which can be used to deal with more-complicated intelligence issues. According to the structure and design criteria, a software environment (SEMIPAS), which supports the implementation of multimedia information (image + speech, image + characters, speech + characters, image + speech + characters) processing and analysis applications, is implemented and introduced. Under this software environment, a multimedia information processing and analysis system called “To Know the World” is constructed. Experiments show that the multimedia information processing and analysis is much more powerful and effective than single-medium information processing and analysis.     

基于C#调用CG400实现边缘检测的研究

介绍了基于C#的实时监视和边缘提取的视觉系统.首先利用C#语言实现控制大恒公司的CG400图像采集卡图像存取设置,结合可用C#语言调用的Emgu CV图像处理工具包的Canny函数,实现实时的视频监视与Canny边缘提取.试验得到了良好的效果,在工程中的视觉应用领域中有一定的应用价值.     

基于树状小波分解的纹理图象检索

针对图象检索应具有简单、快速、有效等要求,提出了一种采用树状小波分解特征的纹理图象检索方法,该方法可以在相应的能量准则下,自适应地对图象进行了带分解,同时可利用小波函数分解的多分辨率与多方向特性,来形成能够在一定程度上对图象进行精确描述的特征矢量;在此基础上,又采用基于图象特征值的主分量分析方法,有效降低了特征矢量的维数;另外,基于用户需求的分层检索,还满足了用户不同层次的需求。实验结果表明,该算法快速,有效,具有较强的应用价值。     

Design Considerations for Digital Image Processing Systems

The brightness levels in a scene or image, together with the spatial relationships among these levels, comprise the total input and output data available to the digital image processor. Indeed, in any mathematical image processing operation, these are the elements of the image which are being manipulated and which represent the major concern of the image processing professional. However, many other factors affect image brightness relations and can distort or obscure the outcome of any image processing experiment. These factors, which consist of a long chain of transmitters, transducers, signal conditioners and processors, are in aggregate commonly called the image chain. An understanding of the image chain is essential to the design of image processing systems.     

多核图像处理并行设计范式的研究与应用

多核计算环境下采用图像处理并行算法可提高图像处理的速度,但已有的并行设计只针对边缘检测、图像投影等特定算法进行,没有形成通用的并行算法设计范式。为此,在研究图像处理算法可并行处理机制和多核架构特点的基础上,提出分析、建模、映射、调试和性能评价及测试发布等5个设计步骤的基于多核计算环境的图像处理算法并行设计范式,以图像傅里叶变换并行算法设计为例在单核、双核、四核、八核计算环境下验证了该并行范式的有效性。实验结果表明,该范式在图像处理并行设计方面可扩展图像处理的应用空间。     

Simulating Spatially Explicit Problems on High Performance Architectures

This paper addresses issues of implementation and performance optimization of simulations designed to model spatially explicit problems with the use of parallel discrete event simulation. A simulation system is presented that uses the optimistic protocol and runs on a distributed memory machine—the IBM SP. The efficiency of parallel discrete event simulations that use the optimistic protocol is strongly dependent on the overhead incurred by rollbacks. This paper introduces a novel approach to rollback processing which limits the number of events rolled back as a result of a straggler or antimessage. The method, called Breadth-First Rollback (BFR), is suitable for spatially explicit problems where the space is discretized and distributed among processes and simulation objects move freely in the space. The BFR uses incremental state saving, allowing the recovery of causal relationships between events during rollback. These relationships are then used to determine which events need to be rolled back. This paper presents an application of BFR to the simulation of Lyme disease. Our results demonstrate and almost linear speedup—a dramatic improvement over the traditional approach to rollback processing. Additionally, BFR is used as a basis of a dynamic load balancing algorithm that migrates load between the simulation processes. A brief outline of the algorithm and its potential performance are presented.     

Threshold superposition in morphological image analysis systems

It is shown that four composite morphological systems, namely morphological edge detection, peak/valley extraction, skeletonization, and shape-size distributions obey a weak linear superposition, called threshold-linear superposition. The output image signal or measurement from each system is shown to be the sum of outputs due to input binary images that result from thresholding the input gray-level image at all levels. These results are generalized to a vector space formulation, e.g. to any finite linear combination of simple morphological systems. Thus many such systems processing gray-level images are reduced to corresponding binary image processing systems, which are easier to analyze and implement     

Generalized Rough Sets, Entropy, and Image Ambiguity Measures

Quantifying ambiguities in images using fuzzy set theory has been of utmost interest to researchers in the field of image processing. In this paper, we present the use of rough set theory and its certain generalizations for quantifying ambiguities in images and compare it to the use of fuzzy set theory. We propose classes of entropy measures based on rough set theory and its certain generalizations, and perform rigorous theoretical analysis to provide some properties which they satisfy. Grayness and spatial ambiguities in images are then quantified using the proposed entropy measures. We demonstrate the utility and effectiveness of the proposed entropy measures by considering some elementary image processing applications. We also propose a new measure called average image ambiguity in this context.     

A parallel architecture for discrete relaxation algorithm

Discrete relaxation techniques have proven useful in solving a wide range of problems in digital signal and digital image processing, artificial intelligence, operations research, and machine vision. Much work has been devoted to finding efficient hardware architectures. This paper shows that a conventional hardware design for a Discrete Relaxation Algorithm (DRA) suffers from O(n2m3) time complexity and O(n2m2) space complexity. By reformulating DRA into a parallel computational tree and using a multiple tree-root pipelining scheme, time complexity is reduced to O(nm), while the space complexity is reduced by a factor of 2. For certain relaxation processing, the space complexity can even be decreased to O(nm). Furthermore, a technique for dynamic configuring an architectural wavefront is used which leads to an O(n) time highly concurrent DRA3 architecture.     

An array processing language for transputer networks

Networks of transputers are often used for array processing applications. Programming such systems in OCCAM can be tedious and error-prone. This paper outlines a language designed to facilitate the solution of problems which involve some array processing. The language is called LATIN, and is currently being implemented on a transputer network. An example of its use is given.     

基于多尺度top-hat变换的自适应彩色图像增强

针对传统彩色图像增强过程中的过度增强及空间变化所引起的信息丢失现象,在RGB空间提出一种基于数学形态学top-hat算法,以各分量标准差权重比例为调控因子的彩色图像增强方法。首先,提取R、G、B通道多尺度下的亮、暗细节特征,然后利用控制因子对有应用价值的细节特征进行增强,最后组合三个分量,得到增强的目标图像。实验结果表明,该方法能有效增强图像对比度,避免过度增强,且能很好地保持亮度,视觉效果良好。     

The simplicial neural cell and its mixed-signal circuit implementation: an efficient neural-network architecture for intelligent signal processing in portable multimedia applications

This paper introduces a novel neural architecture which is capable of similar performance to any of the "classic" neural paradigms while having a very simple and efficient mixed-signal implementation which makes it a valuable candidate for intelligent signal processing in portable multimedia applications. The architecture and its realization circuit are described and the functional capabilities of the novel neural architecture called a simplicial neural cell are demonstrated for both regression and classification problems including nonlinear image filtering.     

基于OpenCV的管道巡检水下机器人的设计与实现

本设计是基于OpenCV的管道巡检水下机器人的设计与实现,水下机器人通过所配备的OpenCV摄像头对水下管道进行探测,主要应用于对水下或海底管道的路线进行循迹,并且能够对外壁破损情况的检查以及清理附着的杂物。该设计的实现是应用OpenCV摄像头对所需巡检的管道进行探测,并将所探测到的图像反馈到STM32控制器中识别出管道的循迹路线,并通过驱动模块中的电机设计实现平稳的循迹以及转弯功能。最终通过水下机器人的循迹以及图像处理功能的设计将探测到管道外部轮廓的图像信息进行处理,突出外壁所存在的问题以及附着的杂物。本设计将水下机器人驱动模式与图像处理功能进行很好的结合与应用,从而实现对管道循迹的过程中管道外壁的收检测。     

Analysing fundamental properties of marker-based vision system designs

This paper investigates fundamental properties of marker-based vision (MBV) systems. We present a theoretical analysis of the performance of basic tag designs which is extended through simulation to investigate the effects of different processing algorithms. Real-world data are processed and related to the simulated results. Image processing is performed using Cantag, an open-source software toolkit for building marker-based vision (MBV) systems that can identify and accurately locate printed markers in three dimensions. Cantag supports multiple fiducial shapes, payload types, data sizes and image processing algorithms in one framework. This paper explores the design space of tags within the Cantag system, and describes the design parameters and performance characteristics which an application writer can use to select the best tag system for any given scenario.