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HalconMachineVision-basedTestP
- 所上载的内容是一篇基于halcon的机器视觉试验平台的设计与研究的文章,它对于想用halcon从事类似工作的读者很有用。,Set up by the contents of Halcon are based on a test platform for machine vision design and research articles, it want to engage in similar work with Halcon readers very useful.
Geneticalgorithm
- 传算法的基本原理、设计方法及其并行实现，以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络-Propagation algorithm of the basic principles, design methods and their parallel implementation, as well as in combinatorial optimization, machine learning, image processing, process control, evoluti
Machinevisionsystemdesignmethods
- 机器视觉系统设计方法，相信对初学者有一定帮助！-Machine vision system design methods, I believe that some help for beginners!
restore
- 图像增强的目标是改进图片的质量，例如增加对比度，去掉模糊和噪声，修正几何畸变等；图像复原是在假定已知模糊或噪声的模型时，试图估计原图像的一种技术。 图像增强按所用方法可分成频率域法和空间域法。前者把图像看成一种二维信号，对其进行基于二维傅里叶变换的信号增强。采用低通滤波（即只让低频信号通过）法，可去掉图中的噪声；采用高通滤波法，则可增强边缘等高频信号，使模糊的图片变得清晰。具有代表性的空间域算法有局部求平均值法和中值滤波（取局部邻域中的中间像素值）法等，它们可用于去除或减弱噪声。 -A
matlab
- 模式识别中的线性分类器的设计，包括感知机，最小二乘法和支撑矢量机的算法的MATLAB代码。-Pattern Recognition linear classifier design, including perception, least squares and support vector machine algorithm MATLAB code.
10
- 本文提出了一种基于学习的相似性度量方 法, 即将图像配准的度量问题转化为模式分类问题, 由基于机器学习设计的分类器自动检验图像是否配准. 本文对400 组图像进行了配准检验, 实验结果显示了该方法的可行性和可靠性.-This paper proposes a similarity measure based on learning methods, about the measurement problems of image registration into the pattern c
EmbedMachineVisionControlSys
- 嵌入式机器视觉测控系统，视觉工具的研究与开发，结合嵌入式，述说了机器视觉的算法与应用，设计了机器测控系统的软件设计与调试。-Embedded machine vision control system, visual tool for research and development, combined with embedded, describing the application of machine vision algorithms and the design of the mach
pdn_src_3_10
- 手头有图片要处理，但是机器上没有安装Photoshop？那就来试试“迷你版Photoshop” - Paint.NET吧。 Paint.NET是一款由美国华盛顿州大学开发，为微软官方支持的一个高级研究生设计项目，旨在为用户提供一个免费的强大的微软绘图板替代软件。不过随着Paint.NET项目的深入研发，Paint.NET的表现已经远远超于最初的目标，无论是从功能上还是效率上都已经达到了一款专业图形处理软件的水准。 -Pictures on hand to deal with, but n
Pattern-Design-System
- 本体统为实现纹织图案的电脑快速设计而构建，应用了先进的图像处理技术，用简便的菜单来实现对纺织图案的设计，并能保存成直接被纺织机识别使用的上级文件。-The jacquard pattern of decency to achieve rapid design and build the computer, the application of advanced image processing technology to achieve with a simple menu design of
svm-ses
- 分别采用感知机算法、最小平方误差算法、线性SVM算法设计分类器，分别画出决策面，并比较性能。-The machine algorithm respectively perception, the minimum square error algorithm, linear SVM classifier algorithm design, respectively, draw the decision surface, and compare the performance.
6.5
- 08级燕山大学电气工程学院测控技术与仪器专业本科毕业设计 基于机器视觉的运动车辆研究-08 Yanshan University, Electrical Engineering Control Technology and Instrument Bachelor degree in design of machine vision-based movement of vehicles
2CviImage
- 实现简单的灰度处理,主要调用BItmap函数库的内容，实现位处理功能。-This system mainly uses LabWindows/CVI and the visual software package Vision design system program. Vision has a wide range of machine vision development environment, the visual software package Vision machine vis
GUI-calib
- 张正友相机标定程序，带GUI设计界面，标定精度可以满足一般的机器视觉要求。-Zhang Zhengyou camera calibration program with GUI interface design, calibration accuracy to meet the general requirements of machine vision.
matlab
- 支持向量机目标分类算法的设计与实现（图像分类）-Design and implementation of support vector machine in target classification algorithm (image classification)
cml
- 基于机器视觉的饮料瓶盖缺陷检测算法设计，包括GUI界面-Design of detection algorithm for drink bottle cap defects based on machine vision
Feature-point-classification
- 图形图像处理与机器视觉以及MATLAB的图像化用户界面设计以及surf算法-Graphic image processing and machine vision as well as MATLAB graphical user interface design and surf algorithm
face_rec
- ## 人脸识别GUI设计 这是我在理解PCA算法后，设计`MATLAB GUI`实现人脸识别。 ### 使用方法： 1. 运行face.m主脚本 2. 点击`训练机器`选择train文件夹 3. 点击`choose photo`选择test文件夹下的一张图片 4. 最后点击`recognize`即可进行识别 5. 点击`Accuracy`可计算整个test文件夹下所有图识别准确率 ###(## face recognition GUI design This i
kaiheng-V6.4
- Based on matlab GUI interface design, Multi-machine power system simulation and flow calculation, Multi-target tracking particle filter.
Recenatioolutionon
- Recent innovations in training deep convolutional neural network models have motivated the design of new methods to automatically learn local image descriptors. The latest deep ConvNets proposed for this task consist(from machine learning show that