快速显微图象处理计算机系统的输入／输出设计

本文从软件、硬件功能的角度,描述了快速显微图象处理系统的输入、输出的设计,它是一个用于快速显微图象计算机上的、智能化的显微视觉控制系统,能广泛的用于生物医学、环保、木材、金相、指纹等分析识别的图象处理系统中。     

图象技术及其应用

图象技术是当前计算机的热门技术之一。本文重点讨论了图象的输入、输出、存储和图象处理等关键性技术。并对图象技术的应用前景加以讨论。     

CROMEMCO微机图象接口SDD与SDI的开发

本文对 CROMEMCO 微机图象接口板 SDD 与 SDI 进行了研究,并分别开发作为图象输入和图象输出接口部件。所构造的图象处理系统在一些应用研究中获得满意效果。     

森林火情监测系统(二)

4)图象处理系统它暂存图象,产生视频信号以驱动显示监视器的,从视频输入设备数字化视频信号,并完成图象数据的强度变换,它能实时或准实时地完成图象数字运算.可适用的系统列于下: ①I~2S Model 75系统、它是一个通用图象阵列处理的,可完成种类图象处理算法,递归空间处理为卷积、滤波和分类以及复杂的几何运算和绘图输出.     

Color Sync色彩管理系统

从事桌面排版和多媒体制作的用户都知道,在图象处理过程中,图象的输入、处理和输出三个环节分别需要由不同的设备来实施,由于这些设备处理颜色的方法不尽相同,不可避免地会导致最终输出和最初输入之间的色彩差异。要确保输入和输出图象具有一致的色彩,就必须协调好各种设备之间的色彩管理,这就是色彩管理系统的用武之地。     

PA-1型微型机花形分析系统

PA-1系统是一个简易的图象处理系统,它为电子提花针织机的花形制备提供了计算机辅助设计的手段。该系统由微型计算机、图象输入设备、接口电路、系统控制软件和图象处理软件等组成。本文介绍该系统的硬件、软件的原理和结构。     

CIMP—1微型计算机图象处理系统简介

CIMP—1微型计算机图象处理系统是以Z—2H微型计算机为基础,采用自己研制的TVC—1图象输入设备,以及由输出接口电路和普通彩色监视器组成的图象输出设备联机构成的图象处理系统。该系统可以把场景、图片、照片、显微图片等图象信息变换成数字信号送入电子计算机,进行各种处理后在彩色电视机监示器上显示出来,借以直接评价处理效果。     

第二讲 数字图象处理在微机上的实现

一、实现数字图象处 理的硬件环境 数字图象处理与其他数据处理的不同之处是数据量大和图象显示,无论是硬件系统构成,还是软件配置均有别于其他数据处理设备,出现了专为数字图象处理而开发的数字图象处理系统(数字图象有时也简称为图象)。 1.数字图象处理系统的发展 以计算机为核心的数字图象处理     

用C＋＋设计Windows图象处理软件

一、概述 目前国外多数微机版图象处理都是基于Windows的,如国内流行的Adobe PhotoShop,PhotoStyler以及许多扫描仪的配套软件。在这里,作者提出一种基于面向对象的处理软件的设计原理,它使我们在Windows下的图象输入、输出,和高级用户界面设计方面变得简单。作者用的开发工具为Bor-land C~( )3.1。读者也可以基于这种思想在Borland C~( ) 4.0,Microsoft C~( )7.0或Visual C~( )上进行图象处理软件设计。 二、Windows环境中 的图象处理     

七十年代医疗图象信息处理的两大技术进展

概述 医疗图象信息处理是模式识别、图象处理这一新学科的一个非常重要的组成部分,它识别和处理医疗二维图象。用各种记录器、X射线照相、超声波全息照、飞点扫描器等得到的医疗图象见图1。     

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     

Theoretical foundations of spatially-variant mathematical morphology part ii: gray-level images

In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the Euclidean space. The proposed theory preserves the geometrical concept of the structuring function, which provides the foundation of classical morphology and is essential in signal and image processing applications. We define the basic SV gray-level morphological operators (i.e., SV gray-level erosion, dilation, opening, and closing) and investigate their properties. We demonstrate the ubiquity of SV gray-level morphological systems by deriving a kernel representation for a large class of systems, called V-systems, in terms of the basic SV graylevel morphological operators. A V-system is defined to be a gray-level operator, which is invariant under gray-level (vertical) translations. Particular attention is focused on the class of SV flat gray-level operators. The kernel representation for increasing V-systems is a generalization of Maragos' kernel representation for increasing and translation-invariant function-processing systems. A representation of V-systems in terms of their kernel elements is established for increasing and upper-semi-continuous V-systems. This representation unifies a large class of spatially-variant linear and non-linear systems under the same mathematical framework. Finally, simulation results show the potential power of the general theory of gray-level spatially-variant mathematical morphology in several image analysis and computer vision applications.     

一种基于灰度级相位的指纹图像增强方法

图像增强是指纹识别系统中非常重要的一个步骤。本文提出了灰度级相位的概念,并实现了一个根据灰度级相位增强指纹图像的方法。该方法首先计算指纹区域内每个像素点的灰度级相位,然后对灰度级相位进行滤波,最后根据滤波后的灰度级相位构建指纹图像。测试结果表明该方法对低质量的指纹图像增强效果好。     

复杂背景下的阈值插值方法

图像分割是进行图像处理的关键步骤。目前很多图像分割的技术都需要人工干预，而且是针对单纯的图像背景才能达到目标。为了解决有复杂背景的图像的分割问题，采用自适应阈值(阈值插值)的方法，并对其加以改进，用迭代阈值判断子图像的直方图是否是双峰分布，同时确定直方图有双峰的子图像的阈值；用双线性插值的方法确定直方图非双峰分布的予图像的阈值，使这种算法在实际中可行。实验证明这种方法适用于复杂背景的图像分割，且通用性比较好。     

一种低成本的视频数字图象获取方法在微计算机系统中的实现

本文阐述一种用二值影象组合装配获取视频数字图象的方法.按照这一方法,用标准电视摄象机和八位微处理器实现了一个价廉而灵活的微计算机图象处理系统.文中给出了系统视频图象输入接口结构框图及软件操作命令.该系统获取图象的最大能力为256×256,十六灰度级;具有两种可以灵活选择的程序控制方式;以每灰度级40ms的速度输入局部图象,或以每灰度级1800ms的速度(采用2MHz的8080A MPU)获取整幅图象.     

三维视觉测量系统平台的软件设计及实现

主要阐述了三维视觉测量系统的软件设计及实现,包括4个部分：图像卡的二次开发、电移台运动控制、图像处理、摄像机标定;利用VC＋＋实现了图像卡的二次开发和电移台运动的实时控制;利用MATLAB强大的矩阵运算能力,与VC＋＋相结合,实现了图像处理和摄像机内外参数的标定;通过实验表明,本系统运行正常,为进一步研究三维视觉自标定、不标定理论和实现在线测量提供了一个好的平台。     

Feature subset selection and feature ranking for multivariate time series

Feature subset selection (FSS) is a known technique to preprocess the data before performing any data mining tasks, e.g., classification and clustering. FSS provides both cost-effective predictors and a better understanding of the underlying process that generated the data. We propose a family of novel unsupervised methods for feature subset selection from multivariate time series (MTS) based on common principal component analysis, termed CLeVer. Traditional FSS techniques, such as recursive feature elimination (RFE) and Fisher criterion (FC), have been applied to MTS data sets, e.g., brain computer interface (BCI) data sets. However, these techniques may lose the correlation information among features, while our proposed techniques utilize the properties of the principal component analysis to retain that information. In order to evaluate the effectiveness of our selected subset of features, we employ classification as the target data mining task. Our exhaustive experiments show that CLeVer outperforms RFE, FC, and random selection by up to a factor of two in terms of the classification accuracy, while taking up to 2 orders of magnitude less processing time than RFE and FC.     

基于C64x的红外双波段图像融合处理系统的设计与实现*

设计并实现了一种红外双波段图像融合系统,该系统采用高性能的TMS320C6414 DSP进行图像处理,通过FPGA实现的Link口以LVDS信号进行图像数据传输,满足了图像融合系统中图像处理能力和图像数据通信能力的要求。在硬件系统的基础上,还专门设计开发了系统监控软件,实时监控系统状态,实时管理并分配系统资源,为图像处理算法提供一个可靠、高效、方便的工作平台。     

Inverse error-diffusion using iterated conditional modes

Error-diffusion (ED) is one conventional halftoning technique that converts a gray-level image into a halftone. For further processing the ED halftones, it is often necessary to estimate the original image from the halftone: the inverse of ED. We propose to calculate iterated conditional modes (ICM) for the maximum a posteriori (MAP) solution of inverse ED. The ICM always searches for a better estimate in the valid image space. It requires only local computation and is applicable to any type of the MRF model used for the original gray-level images. Experimental results for common standard images are given to show that our ICM performs well and is more flexible than the descent-projection (DP) approach.     

Using artificial intelligence planning to automate science image data analysis

In recent times, improvements in imaging technology have made available an incredible array of information in image format. While powerful and sophisticated image processing software tools are available to prepare and analyze the data, these tools are complex and cumbersome, requiring significant expertise to properly operate. Thus, in order to extract (e.g., mine or analyze) useful information from the data, a user (in our case a scientist) often must possess both significant science and image processing expertise.This article describes the use of artificial intelligence (AI) planning techniques to represent scientific, image processing and software tool knowledge to automate knowledge discovery and data mining (e.g., science data analysis) of large image databases. In particular, we describe two fielded systems. The Multimission VICAR Planner (MVP) which has been deployed for since 1995 and is currently supporting science product generation for the Galileo mission. MVP has reduced time to fill certain classes of requests from 4 h to 15 min. The Automated SAR Image Processing system (ASIP) was deployed at the Department of Geology at Arizona State University in 1997 to support aeolian science analysis of synthetic aperture radar images. ASIP reduces the number of manual inputs in science product generation by ten-fold.