<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[CptOctopus的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/CptOctopus</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; CptOctopus]]></copyright><item><title><![CDATA[OpenCV学习-P48 SITF算法和SURF算法]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127905374</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127905374</guid><author>CptOctopus</author><pubDate>Tue, 07 Feb 2023 16:50:52 +0800</pubDate><description><![CDATA[OpencvSIFT算法及SURF算法学习]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P59 视频读写]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/128827430</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/128827430</guid><author>CptOctopus</author><pubDate>Wed, 01 Feb 2023 10:37:40 +0800</pubDate><description><![CDATA[opencv视频读写]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P44 角点检测]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127880212</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127880212</guid><author>CptOctopus</author><pubDate>Thu, 17 Nov 2022 15:51:12 +0800</pubDate><description><![CDATA[角点检测]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P40 霍夫变换]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127690443</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127690443</guid><author>CptOctopus</author><pubDate>Wed, 09 Nov 2022 11:27:18 +0800</pubDate><description><![CDATA[霍夫变换直线及圆检测]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P39 Opencv模板匹配]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127689406</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127689406</guid><author>CptOctopus</author><pubDate>Fri, 04 Nov 2022 15:30:35 +0800</pubDate><description><![CDATA[opencv模板匹配]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P34-P38 Opencv边缘检测]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127565070</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127565070</guid><author>CptOctopus</author><pubDate>Fri, 04 Nov 2022 15:04:14 +0800</pubDate><description><![CDATA[opencv边缘检测]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P29-P32 Opencv直方图均衡化、掩膜]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127533740</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127533740</guid><author>CptOctopus</author><pubDate>Thu, 27 Oct 2022 16:22:16 +0800</pubDate><description><![CDATA[opencv直方图均衡化]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P24-P28 Opencv滤波]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127514420</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127514420</guid><author>CptOctopus</author><pubDate>Wed, 26 Oct 2022 15:33:39 +0800</pubDate><description><![CDATA[OpenCV滤波]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P19-P23 Opencv形态学操作总结]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127495330</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127495330</guid><author>CptOctopus</author><pubDate>Tue, 25 Oct 2022 15:24:26 +0800</pubDate><description><![CDATA[OpenCV学习-P19-P23 Opencv形态学操作总结]]></description><category></category></item><item><title><![CDATA[OpenCV学习-P4-P18 Opencv基本操作介绍及图像基础处理]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/127446769</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/127446769</guid><author>CptOctopus</author><pubDate>Mon, 24 Oct 2022 16:24:04 +0800</pubDate><description><![CDATA[Opencv学习笔记]]></description><category></category></item><item><title><![CDATA[24. 区域处理综合例程]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/122927480</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/122927480</guid><author>CptOctopus</author><pubDate>Tue, 15 Feb 2022 16:36:11 +0800</pubDate><description><![CDATA[区域处理综合例程

]]></description><category></category></item><item><title><![CDATA[23. 区域仿射变换]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/122927247</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/122927247</guid><author>CptOctopus</author><pubDate>Mon, 14 Feb 2022 16:32:21 +0800</pubDate><description><![CDATA[区域仿射变换
步骤：
1.创建二维变换矩阵：hom_mat2d_identity（HomMat2DIdentity）,HomMat2DIdentity为单位 矩阵
2.创建变换矩阵
位移变换：hom_mat2d_translate(HomMat2DIdentity, 100, 100, HomMat2DTranslate)
旋转变换hom_mat2d_rotate
平移变换
缩放变换
等等
3.执行变换操作
affine_trans_region(Region1, RegionAffineTrans, Ho]]></description><category></category></item><item><title><![CDATA[造球粒径检测算法论文阅读笔记]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/119861816</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/119861816</guid><author>CptOctopus</author><pubDate>Thu, 02 Dec 2021 10:47:14 +0800</pubDate><description><![CDATA[造球粒径检测算法论文阅读笔记1.图像感兴趣区域的划分2.生球区图像高斯滤波3.生球区域与阴影区域的分割对生球区域的分类标记(区分上下层球)
1.图像感兴趣区域的划分
依据光照的不同，将图像区域分为两类，一是ABEF,CDGH,二是BFGC，且论文中说，这两区域的参数取相同值

2.生球区图像高斯滤波
图像的灰度的分布呈山峰状，每个“山峰”表示单个生球表面的灰度分布，这种分类类似于高斯分布，为了保持表面灰度分布的高斯分布特征，所以采用高斯滤波的方法

高斯滤波在滤波过程中，用大小为l∗hl*hl∗h的模板扫描]]></description><category></category></item><item><title><![CDATA[C# Windows服务程序编写]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/120717165</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/120717165</guid><author>CptOctopus</author><pubDate>Thu, 02 Dec 2021 10:47:07 +0800</pubDate><description><![CDATA[C#  Windows服务程序编写 1.新建windows service 项目2.添加安装程序代码移植
系统信息：Windows 10，.Net Framework 4.5.2 ，visual studio 2019, 程序架构X86，halcon和opcdll均为32位
1.新建windows service 项目

2.添加安装程序
在Service.cs页面右键 添加安装程序 即可添加serviceProcessInstaller1和serviceinstaller1两个安装组件
修改service]]></description><category></category></item><item><title><![CDATA[22. 区域几何变换]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/120799142</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/120799142</guid><author>CptOctopus</author><pubDate>Thu, 11 Nov 2021 18:53:28 +0800</pubDate><description><![CDATA[区域几何变换
1.区域平移，可用来求区域某个方向的边界
具体思路为，先使用boundary（）求区域边界，然后将区域移动，最后将移动后的区域与boundary做intersection

例如，求某绣花针针头的三个位置的粗细，如下图中间所示，因为绣花针在镜头里的具体位置不确定，所以先要找到针头最上端的位置，然后往下移动固定距离再构造矩形与绣花针边界作intersection得左右两个边界region，然后在求region之间的距离即为宽度求宽度


2.包括转置、镜像，不赘述
3.极坐标变换，将圆形分布转换]]></description><category></category></item><item><title><![CDATA[13. 区域间距离计算]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/120362729</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/120362729</guid><author>CptOctopus</author><pubDate>Sat, 18 Sep 2021 14:03:35 +0800</pubDate><description><![CDATA[区域间距离计算
1.点和点之间的距离计算
distance_pp (Row1,Column1 ,Row2 ,Column2 , Distance)

2.点到直线的距离
distance_pl()

3.点到区域的距离
distance_pr()

4线到区域的距离
distance_lr()

5.区域到区域的最短距离
disatance_rr_min()

例：求O到L的距离

1.先找出大矩形区域

2.对该区域做二值化分割

3.利用外接圆半径提取出矩形边界，注意可以多利用外接圆半径少用面积，而且每]]></description><category></category></item><item><title><![CDATA[12. 区域生成保存读取]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/120361348</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/120361348</guid><author>CptOctopus</author><pubDate>Sat, 18 Sep 2021 09:48:44 +0800</pubDate><description><![CDATA[区域生成保存读取
区域可以保存为HOBJ文件
使用concat_obj可以组合两个区域,或者向空区域中添加对象
*保存区域
write_region(Rctangle,'region.hobj')
*读取区域
reduce_domain(Image,RegionRoi,ImageReduced)
concat_obj(RegionRoi,Circle2,RegionRoi)


...]]></description><category></category></item><item><title><![CDATA[11. ROI例程：金属件正反面检测]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/119450955</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/119450955</guid><author>CptOctopus</author><pubDate>Fri, 17 Sep 2021 10:08:07 +0800</pubDate><description><![CDATA[ROI例程：金属件正反面检测

]]></description><category></category></item><item><title><![CDATA[10.区域形态学]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/119427145</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/119427145</guid><author>CptOctopus</author><pubDate>Fri, 06 Aug 2021 10:35:20 +0800</pubDate><description><![CDATA[区域形态学主要包括：
主要包括：
shape_trans:根据区域产生指定图形
skeleton:求区域骨架

]]></description><category></category></item><item><title><![CDATA[7.8.9.BLOB分析及流程,图像分割出区域，区域集合运算及特征筛选]]></title><link>https://blog.youkuaiyun.com/CptOctopus/article/details/119419802</link><guid>https://blog.youkuaiyun.com/CptOctopus/article/details/119419802</guid><author>CptOctopus</author><pubDate>Thu, 05 Aug 2021 17:10:56 +0800</pubDate><description><![CDATA[7.8.9.BLOB分析及流程,图像分割出区域，区域集合运算及特征筛选BLOB分析及流程阈值分割的方法区域集合运算及特征筛选形态学运算：开、闭、膨胀、腐蚀，集合运算：union(并)、difference（减）、intersection（交）
BLOB分析及流程
以ball例子为例
流程如下：
读取图片-&gt;找产品(即焊板)-&gt;缩小区域聚焦于产品上-&gt;阈值分割-&gt;根据特征找焊点(即圆形，使用圆进行开运算)-&gt;统计形状
灰度直方图：可以滑动两端的线控制哪个灰度值的区域显示

阈值分]]></description><category></category></item></channel></rss>