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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。 相似文献
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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。 相似文献
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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. 相似文献
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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。 相似文献
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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。 相似文献
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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 相似文献
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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 相似文献
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Threshold superposition in morphological image analysis systems 总被引:3,自引:0,他引:3
Maragos P. Ziff R.D. 《IEEE transactions on pattern analysis and machine intelligence》1990,12(5):498-504
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 相似文献
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Bouaynaya N Schonfeld D 《IEEE transactions on pattern analysis and machine intelligence》2008,30(5):837-850
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. 相似文献
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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. 相似文献
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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。 相似文献
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Yoon H. Yang K. Shahabi C. 《Knowledge and Data Engineering, IEEE Transactions on》2005,17(9):1186-1198
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. 相似文献
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Ken-Chung Ho 《Displays》2009,30(4-5):175-184
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. 相似文献
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《Intelligent Data Analysis》1999,3(3):159-176
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. 相似文献