登录
首页 » C# » C# 使用Halcon进行模板匹配定位

C# 使用Halcon进行模板匹配定位

于 2020-07-02 发布 文件大小:4891KB
0 230
下载积分: 1 下载次数: 108

代码说明:

  C# 使用Halcon进行模板匹配定位(C# uses Halcon for template matching and location)

文件列表:

Machine Vision
Machine Vision\Machine Vision
Machine Vision\Machine Vision\bin
Machine Vision\Machine Vision\bin\Debug
Machine Vision\Machine Vision\bin\Debug\Config
Machine Vision\Machine Vision\bin\Debug\Config\Config.ini, 50, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\halcondotnet.dll, 1279632, 2016-02-25
Machine Vision\Machine Vision\bin\Debug\halcondotnet.xml, 4078287, 2016-02-25
Machine Vision\Machine Vision\bin\Debug\Log
Machine Vision\Machine Vision\bin\Debug\Machine Vision.exe, 157696, 2016-09-08
Machine Vision\Machine Vision\bin\Debug\Machine Vision.pdb, 163328, 2016-09-08
Machine Vision\Machine Vision\bin\Debug\Machine Vision.vshost.exe, 22472, 2016-09-08
Machine Vision\Machine Vision\bin\Debug\Result
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111203.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111401.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111407.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111412.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111414.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111416.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111418.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111425.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111427.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111431.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111432.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_111435.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112154.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112156.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112158.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112200.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112220.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112221.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_112243.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113635.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113640.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113644.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113650.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113653.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113655.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113656.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113658.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113701.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_113703.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160904_115936.bmp, 685222, 2016-09-04
Machine Vision\Machine Vision\bin\Debug\Result\20160905_102845.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104025.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104030.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104044.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104249.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104406.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104502.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104504.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104505.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104516.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104721.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104745.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104922.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104923.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104931.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_104948.bmp, 693398, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115610.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115613.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115615.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115618.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115620.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115625.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115627.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_115629.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120156.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120350.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120355.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120358.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120359.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120434.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160905_120439.bmp, 685222, 2016-09-05
Machine Vision\Machine Vision\bin\Debug\Result\20160906_073433.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_073455.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_073849.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_073859.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_090001.bmp, 789686, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_090032.bmp, 789686, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_090036.bmp, 789686, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_091741.bmp, 768678, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_092808.bmp, 726006, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_101159.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_101306.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_101310.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_101311.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_101312.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102045.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102046.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102048.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102050.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102055.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102057.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_102610.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_104748.bmp, 564750, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_120449.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_120501.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_120511.bmp, 685222, 2016-09-06
Machine Vision\Machine Vision\bin\Debug\Result\20160906_120520.bmp, 678582, 2016-09-06

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • Fourier-Descriptor
    Solutions to problems in the field of digital image processing generally require extensive experimental work involving software simulation and testing with large sets of sample images.
    2012-05-07 01:58:07下载
    积分:1
  • ditonglvbo
    本文件是有关低通滤波器的程序,主要介绍了高斯低通滤波器。(This document is related to the low-pass filter procedure, introduces the Gaussian low-pass filter.)
    2014-03-14 19:52:51下载
    积分:1
  • 小波分析
    说明:  用来做小波分析,开源程序,可画出小波功率谱,小波全谱,程序中有参考文件的网址,非常方便·新手使用(Used to do wavelet analysis, open source program, can draw the wavelet power spectrum, wavelet full spectrum, the program has a reference file of the website, very convenient for beginners to use)
    2021-01-29 15:54:18下载
    积分:1
  • 27220065
    利用正交匹配跟踪原子库对信号进行稀疏分解程序(Using orthogonal matching pursuit atom libraries for signal sparse decomposition process)
    2016-01-01 13:31:26下载
    积分:1
  • BandeletsTutorial[1]
    The second generation bandelets [Peyr´ e and Mallat 2005c] is a orthogonal multiscale transform that is able to capture thegeometric content of images and surfaces.
    2012-06-07 11:44:26下载
    积分:1
  • TrackMe
    人的移动的跟踪,VERILOG实现,能跟踪人的画面移动(Tracking the movement of people, VERILOG realize that can track the person)
    2021-04-29 15:48:43下载
    积分:1
  • imjudge
    转换图象为二值图象后,进行识别与标记的matlab源码。可以计算目标物个数,形心等。(image conversion value for the two images, identification and marking of Matlab source. Can be calculated from the number of goals, such as heart-shaped.)
    2006-11-13 09:54:44下载
    积分:1
  • ImageCutofRGB565BMP
    裁剪以RGB565格式保存的BMP文件,涉及位图掩码内容(imagecut of the BMP picture which saved with RGB565 format and mask)
    2015-01-22 10:57:48下载
    积分:1
  • ggongzhennQo
    gongzhenQ.m:计算双稳态随机共振系统输入输出信信噪比增益,非常明显的随机共振现象。,已通过测试。 (gongzhenQ.m: calculation of the stochastic resonance of bistable stochastic resonance system input output signal SNR gain, it is clear. , Has been tested.)
    2012-06-09 10:49:43下载
    积分:1
  • chepaidingwei
    使用说明 使用时打开此例题目录下pic中的图片,然后依次单击按钮“转”、“1”、“2”、“3”、“4”和“5”,就可以实现精确的车牌定位。 具体步骤 1.24位真彩色->256色灰度图。 2.预处理:中值滤波。 3.二值化:用一个初始阈值T对图像A进行二值化得到二值化图像B。 初始阈值T的确定方法是:选择阈值T=Gmax-(Gmax-Gmin)/3,Gmax和Gmin分别是最高、最低灰度值。 该阈值对不同牌照有一定的适应性,能够保证背景基本被置为0,以突出牌照区域。 4.削弱背景干扰。对图像B做简单的相邻像素灰度值相减,得到新的图像G,即Gi,j=|Pi,j-Pi,j-1|i=0,1,…,439 j=0,1,…,639Gi,0=Pi,0,左边缘直接赋值,不会影响整体效果。 5.用自定义模板进行中值滤波 区域灰度基本被赋值为0。考虑到文字是由许多短竖线组成,而背景噪声有一大部分是孤立噪声,用模板(1,1,1,1,1)T对G进行中值滤波,能够得到除掉了大部分干扰的图像C。 6.牌照搜索:利用水平投影法检测车牌水平位置,利用垂直投影法检测车牌垂直位置。 7.区域裁剪,截取车牌图像。()
    2008-06-10 10:17:08下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载