机器视觉在光纤缺陷检测中的应用

目前,光纤已广泛应用于通信领域。光纤连接器作为精密对接光纤两个端面的部件,其重要性不言而喻,传统的端面检测方法是以人工方式对光纤显微镜下的图像是否合格进行判断,不仅精度低,而且效率低下,而利用机器视觉,由计算机来检验可以很好地解决这个问题。     

基于机器视觉的工业检测

针对酒瓶生产中对瓶口进行的有无损伤检测的重要性,对酒瓶瓶口的检测进行深入、系统的研究。基于机器视觉的检测技术通过Halcon软件实现精准度高、过程自动化、速度快的检测,故采用Halcon软件和图像处理的相关算法实现瓶口的准确检测。经过实验表明,采用机器视觉技术,识别的精度和速度有很大的提高,而且减少了人员的使用,从而减少了企业的成本。     

基于机器视觉的工业检测

针对酒瓶生产中对瓶口进行的有无损伤检测的重要性,对酒瓶瓶口的检测进行深入、系统的研究。基于机器视觉的检测技术通过Halcon软件实现精准度高、过程自动化、速度快的检测,故采用Halcon软件和图像处理的相关算法实现瓶口的准确检测。经过实验表明,采用机器视觉技术,识别的精度和速度有很大的提高,而且减少了人员的使用,从而减少了企业的成本。     

基于机器视觉的数据中心机房安全监控系统设计

针对当前校园网数据中心机房人力监控费时费力,传感器式无人监控成本过高的问题,提出了一种基于机器视觉的数据中心机房安全监控方案,分析了该系统的工作流程和特点,介绍了采用背景差分模型实现该系统的设计方案,并进行了测试和分析。测试表明,该系统可达到预期设计的目的。     

基于机器视觉的色差检测算法

针对金属印刷质量中的色差检测问题,采用机器视觉的技术对色差检测算法进行了研究。通过在金属印刷品的留白区域印刷色标,使用工业CCD相机采集金属印刷产品上的色标区域,使用数字图像处理技术提取色标。使用了基于HSV颜色空间的色差检测算法和基于CIELAB颜色空间的色差检测算法,分析了两种颜色空间下色差检测的实验结果,采用两种颜色空间检测算法相结合的方法,实现对色差合理有效的快速检测,同时能保证检测结果的准确性。     

机器视觉的零件轮廓尺寸测量系统设计

提出了一种新的基于机器视觉的零件轮廓尺寸精密测量系统,设计了系统的硬件和软件部分,并介绍了测量系统的关键技术.利用LabVIEW为平台开发系统软件,采用改进的Canny算法识别图像边缘,使得测量速度更快,零件轮廓信息提取效率更高.     

基于机器视觉的焊缝跟踪系统研究与设计

随着制造业的迅速发展,焊接作为一种重要的加工手段发挥着越来越重要的作用,是制造业的重要工序。同时也对焊接的自动化与智能化提出了更高的要求。传统的焊接操作由人工判断焊缝的位置,精度较低且容易引起误判。本文通过对图像采集平台、图像处理算法的研究,提出了一种基于机器视觉处理模块与机器视觉算法的焊缝跟踪系统。通过焊缝特征的提取与处理,控制焊枪实现焊缝的自动跟踪与定位。该系统具有性能稳定、定位精确等特点。     

基于机器视觉的蟋蟀体态测量

设计一套基于机器视觉的蟋蟀体态测量装置,初步研究用图像处理和图像测量的方法实现对蟋蟀躯干长宽的测量.该装置构建一个PC-Based的机器视觉系统,利用VisuaI Basic开发工具编写图像处理算法和图像测量算法的程序.应用惯性主轴的方法实现蟋蟀图片位置的归一化,应用数学形态学分割算法实现了蟋蟀躯干与足和触角的分割,将分割后的躯干进行边缘提取,从而进行蟋蟀体态的测量.     

基于机器视觉的机加工缺陷检测系统设计

本文设计了一个基于机器视觉的机械加工缺陷检测与定位系统,着重阐述了该系统的工作原理,讨论了相关的图像处理、检测及识别算法,仿真实验均用MATLAB编程实现,仿真结果证明了该方法的可行性.采用该方法能够有效的检测、定位并识别出工件表面的缺陷.     

Application of a transparent interface methodology to image processing

Many software engineering projects involve a significant design component in which an algorithm must be formulated as a sequence of processing steps that meets a solution criterion. As the problems tackled become more complex, it becomes increasingly important to create and use tools that help designers understand and manage the design process. We demonstrate the use of design tool called T-STAR in the domain of image processing, in which a toolkit called the TRAnsparent Image Problem Solving Environment (TRAIPSE) is extended to solve face-recognition problems. Key features of TRAIPSE are its visual interface to the space of partial image processing algorithms and its support for automatic assistance in exploring the space. The specific application we present is the analysis of human face images.     

图像分割在医学图像处理中的应用研究

图像分割是图像处理中的重要工作,医学图像的多样性和复杂性使其在图像分割中具有较大的难度。阈值法由于高效、简单而成为图像分割的重要方法,但对于复杂的医学图像,其效果并不很理想。Powell法是最好的直接搜索法,利用改进的Powell法可以更好地搜索目标。为此,提出了一种将Otsu法和Powell法相结合的图像分割方法,仿真实验表明,该方法可以快速有效地分割图像,鲁棒性强。     

Embedded multi-spectral image processing for real-time medical application

The newly introduced Kubelka–Munk Genetic Algorithm (KMGA) is a promising technique for the assessment of skin lesions from multi-spectral images. Using five skin parameter maps such as concentration or epidermis/dermis thickness, this method combines the Kubelka–Munk Light–Tissue interaction model and Genetic Algorithm optimization process to produce a quantitative measure of cutaneous tissue. Up to the present, variant improved KMGA implementations have been successfully realized using the recent parallel computing techniques. However, all these achievements are based on the multi-core CPUs. This results in a quite high cost and low practicability for the hardware equipment of the clinical system. Fortunately, Embedded Systems (ES) applications have made great progress in recent years, and many highly effective image processing devices, such as DSPs (Digital Signal Processor) and FPGAs (Field Programmable Gate Array), have been made available to engineers at a very convenient price. Nevertheless, today’s embedded devices have as well the advantages of high speed, high embedability, low power consumption, more flexibility, etc. Thus, we focus our researches on the embedded KMGA application development. In this paper, we realize the CPU-to-FPGA transplantation of KMGA within a special High-Level Synthesis (HLS) SW/HW Co-design framework. Moreover, several optimizations are made on the algorithm and source code to improve the performances of the final implementation. Compared with CPUs, intensive experiments demonstrate that the proposed approaches can effectively improve the performances of KMGA method both in terms of efficiency and accuracy.     

A methodology for rapid illumination-invariant face recognition using image processing filters

Achieving illumination invariance in the presence of large pose changes remains one of the most challenging aspects of automatic face recognition from low resolution imagery. In this paper, we propose a novel recognition methodology for their robust and efficient matching. The framework is based on outputs of simple image processing filters that compete with unprocessed greyscale input to yield a single matching score between two individuals. Specifically, we show how the discrepancy of the illumination conditions between query input and training (gallery) data set can be estimated implicitly and used to weight the contributions of the two competing representations. The weighting parameters are representation-specific (i.e. filter-specific), but not gallery-specific. Thus, the computationally demanding, learning stage of our algorithm is offline-based and needs to be performed only once, making the added online overhead minimal. Finally, we describe an extensive empirical evaluation of the proposed method in both a video and still image-based setup performed on five databases, totalling 333 individuals, over 1660 video sequences and 650 still images, containing extreme variation in illumination, pose and head motion. On this challenging data set our algorithm consistently demonstrated a dramatic performance improvement over traditional filtering approaches. We demonstrate a reduction of 50–75% in recognition error rates, the best performing method-filter combination correctly recognizing 97% of the individuals.     

High performance medical image processing in client/server-environments

As 3D scanning devices like computer tomography (CT) or magnetic resonance imaging (MRI) become more widespread, there is also an increasing need for powerful computers that can handle the enormous amounts of data with acceptable response times. We describe an approach to parallelize some of the more frequently used image processing operators on distributed memory architectures. It is desirable to make such specialized machines accessible on a network, in order to save costs by sharing resources. We present a client/server approach that is specifically tailored to the interactive work with volume data. Our image processing server implements a volume visualization method that allows the user to assess the segmentation of anatomical structures. We can enhance the presentation by combining the volume visualizations on a viewing station with additional graphical elements, which can be manipulated in real-time. The methods presented were verified on two applications for different domains.     

利用MATLAB实现医学图像处理与分析

介绍了在MATLAB(R2006b)环境下,DICOM医学图像格式的阅读、显示及存储方法,使读者能够了解并熟悉如何在MATLAB环境下使用医学图像处理函数,而没有必要再借用其他的图像格式转换。通过分析这些函数,给出了判断DICOM格式的条件及应用时的注意事项,最后用实例证明了在MATLAB环境中,实现复杂医学图像处理和分析的简洁性及高效性。     

Optimization for limited angle tomography in medical image processing

This paper aims to reduce the problems of incomplete data in computed tomography, which happens frequently in medical image process and analysis, e.g., when the high-density region of objects can only be penetrated by X-rays at a limited angular range. As the projection data are available only in an angular range, the incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. Image reconstruction based on total variation (TV) reduces the problem and gives better performance on edge-preserving reconstruction; however, the artificial parameter can only be determined through considerable experimentation. In this paper, an effective TV objective function is proposed to reduce the inverse problem in the limited angle tomography. This novel objective function provides a robust and effective reconstruction without any artificial parameter in the iterative processes, using the TV as a multiplicative constraint. The results demonstrate that this reconstruction strategy outperforms some previous ones.     

医学图像处理与分析软件平台综述

医学图像处理与分析技术可以给医生提供更清晰、更准确的信息,以利于疾病的诊断和鉴别诊断。医学图像分割、医学图像配准以及三维可视化等算法是医学图像处理与分析发展的源动力,而基于这些算法研发的软件平台是医学图像处理与分析前进的加速器。现有的医学图像处理与分析软件平台极大地便利了医学影像领域的研究者与应用者,大大加快了医学影像发展的步伐。对国内外医学图像处理与分析的软件平台进行了比较系统的归纳,详细地介绍了各类主流软件平台,并充分地讨论了各种平台的优缺点,旨在推广医学图像处理与分析软件平台在国内的应用,并激发国内医学影像领域的研究者为医学图像处理与分析软件平台贡献自己的力量。     

A vision-based statistical methodology for automatically modeling continuous urban traffic flows

We introduce an online video-based virtual sensor allowing to automatically estimate and forecast the number of vehicles passing through a road section over a continuous time interval. The strategy consists, in the first place, in defining a Motion Intensity Index (MII) whose role is to quantify the visual activity in a traffic video. A wavelet-based cause-and-effect statistical model is then used to match the actual number of vehicles to their respective motion scores. This leads to an efficient estimator of the urban traffic flow. The implementation is well optimized in such a way that the local sampling rate is directly proportional to the amount of visual activity in localized sub-shot units of the video. The procedure allows designing an autonomous sensor giving every moment a measure of the flow on a road section and an expectation of its future levels. The device can be very useful for optimizing transportation management, facilitating strategic decision-making, and analyzing networks with the purpose of optimizing transportation equipment efficiency.     

Reconfigurable computing: design methodology and hardware tasks scheduling for real-time image processing

Technology evolution makes possible the integration of heterogeneous components as programmable elements (processors), hardware dedicated blocks, hierarchical memories and buses. Furthermore, an optimized reconfigurable logic core embedded within a System-on-Chip will associate the performances of dedicated architecture and the flexibility of programmable ones. In order to increase performances, some of the applications are carried out in hardware, using dynamically reconfigurable logic, rather than software, using programmable elements. This approach offers a suitable hardware support to design malleable systems able to adapt themselves to a specific application. This article makes a synthesis of the Ardoise project. The first objective of Ardoise project was to design and to produce a dynamically reconfigurable platform based on commercial FPGAs. The concept of dynamically reconfigurable architecture depends partially on new design methodologies elaboration as well as on the programming environment. The platform architecture was designed to be suitable for real-time image processing. The article outlines mainly the Ardoise tools aspect: development environment and real-time management of the hardware tasks. The proposed methodology is based on a dynamic management of tasks according to an application scenario written using C++ language.