Use the OpenCV function :copy_make_border:`copyMakeBorder <>` to set the borders (extra padding to your image).The explanation below belongs to the book Learning OpenCV by Bradski and Kaehler.

  1. In our previous tutorial we learned to use convolution to operate on images. One problem that naturally arises is how to handle the boundaries. How can we convolve them if the evaluated points are at the edge of the image?
  2. What most of OpenCV functions do is to copy a given image onto another slightly larger image and then automatically pads the boundary (by any of the methods explained in the sample code just below). This way, the convolution can be performed over the needed pixels without problems (the extra padding is cut after the operation is done).
  3. In this tutorial, we will briefly explore two ways of defining the extra padding (border) for an image:
    1. BORDER_CONSTANT: Pad the image with a constant value (i.e. black or0)
    2. BORDER_REPLICATE: The row or column at the very edge of the original is replicated to the extra border.

This will be seen more clearly in the Code section.

What does this program do?

  • Load an image
  • Let the user choose what kind of padding use in the input image. There are two options:
  • Constant value border: Applies a padding of a constant value for the whole border. This value will be updated randomly each 0.5 seconds.
  • Replicated border: The border will be replicated from the pixel values at the edges of the original image.
  • The user chooses either option by pressing 'c' (constant) or 'r' (replicate)
  • The program finishes when the user presses 'ESC'

The tutorial code's is shown lines below.

''' file name : border.py
Description : This sample shows how to add border to an image''' import cv2
import numpy as np print " Press r to replicate the border with a random color "
print " Press c to replicate the border "
print " Press Esc to exit " img = cv2.imread('../boldt.jpg')
rows,cols = img.shape[:2]
dst = img.copy() top = int (0.05*rows)
bottom = int (0.05*rows)
left = int (0.05*cols)
right = int (0.05*cols) while(True):
cv2.imshow('border',dst)
k = cv2.waitKey(500)
if k==27:
break
elif k == ord('c'):
value = np.random.randint(0,255,(3,)).tolist()
dst = cv2.copyMakeBorder(img,top,bottom,left,right,
cv2.BORDER_CONSTANT,value = value)
elif k == ord('r'):
dst = cv2.copyMakeBorder(img,top,bottom,left,right,cv2.BORDER_REPLICATE)
cv2.destroyAllWindows()

Explanation

1. Now we initialize the argument that defines the size of the borders (top,bottom,left andright). We give them a value of 5% the size of src.

top = int (0.05*rows)
bottom = int (0.05*rows) left = int (0.05*cols)
right = int (0.05*cols)

2. The program begins a while loop. If the user presses 'c' or 'r', the borderType variable takes the value of BORDER_CONSTANT or BORDER_REPLICATE respectively:

while(True):

    cv2.imshow('border',dst)
k = cv2.waitKey(500)
if k==27:
break
elif k == ord('c'):
value = np.random.randint(0,255,(3,)).tolist()
dst = cv2.copyMakeBorder(img,top,bottom,left,right,cv2.BORDER_CONSTANT,value = value)
elif k == ord('r'):
dst = cv2.copyMakeBorder(img,top,bottom,left,right,cv2.BORDER_REPLICATE)

3. Finally, we call the function :copy_make_border:`copyMakeBorder <>` to apply the respective padding:

copyMakeBorder( src, dst, top, bottom, left, right, borderType, value );

The arguments are:

  • src: Source image
  • dst: Destination image
  • top, bottom, left, right: Length in pixels of the borders at each side of the image. We define them as being 5% of the original size of the image.
  • borderType: Define what type of border is applied. It can be constant or replicate for this example.
  • value: If borderType is BORDER_CONSTANT, this is the value used to fill the border pixels.

输出结果

After compiling the code above, you can execute it giving as argument the path of an image. The result should be:

  • By default, it begins with the border set to BORDER_CONSTANT. Hence, a succession of random colored borders will be shown.
  • If you press 'r', the border will become a replica of the edge pixels.
  • If you press 'c', the random colored borders will appear again
  • If you press 'ESC' the program will exit.

Below some screenshot showing how the border changes color and how the BORDER_REPLICATE option looks:



=====================================================
转载请注明处:http://blog.csdn.net/songzitea/article/details/8698083
=====================================================

【OpenCV】解析OpenCV中copyMakerBorder函数的更多相关文章

  1. (转)解析PHP中ob_start()函数的用法

    本篇文章是对PHP中ob_start()函数的用法进行了详细的分析介绍,需要的朋友参考下     ob_start()函数用于打开缓冲区,比如header()函数之前如果就有输出,包括回车/空格/换行 ...

  2. 【PHP】解析PHP中的函数

    目录结构: contents structure [-] 可变参数的函数 变量函数 回调函数 自定义函数库 闭包(Closure)函数的使用 在这篇文章中,笔者将会讲解如何使用PHP中的函数,PHP是 ...

  3. 解析opencv中Box Filter的实现并提出进一步加速的方案(源码共享)。

    说明:本文所有算法的涉及到的优化均指在PC上进行的,对于其他构架是否合适未知,请自行试验. Box Filter,最经典的一种领域操作,在无数的场合中都有着广泛的应用,作为一个很基础的函数,其性能的好 ...

  4. OpenCV图像处理中常用函数汇总(1)

    //俗话说:好记性不如烂笔头 //用到opencv 中的函数时往往会一时记不起这个函数的具体参数怎么设置,故在此将常用函数做一汇总: Mat srcImage = imread("C:/Us ...

  5. OpenCV中phase函数计算方向场

    一.函数原型 ​该函数参数angleInDegrees默认为false,即弧度,当置为true时,则输出为角度. phase函数根据函数来计算角度,计算精度大约为0.3弧度,当x,y相等时,angle ...

  6. opencv学习笔记之cvSobel 函数解析

    首先,我们来开一下计算机是如何检测边缘的.以灰度图像为例,它的理论基础是这样的,如果出现一个边缘,那么图像的灰度就会有一定的变化,为了方便假设由黑渐变为白代表一个边界,那么对其灰度分析,在边缘的灰度函 ...

  7. opencv学习笔记——cv::CommandLineParser函数详解

    命令行解析类CommandLineParser 该类的作用主要用于命令行的解析,也就是分解命令行的作用.以前版本没这个类时,如果要运行带参数的.exe,必须在命令行中输入文件路径以及各种参数,并且输入 ...

  8. opencv通过dll调用matlab函数,图片作为参数

    [blog 项目实战派]opencv通过dll调用matlab函数,图片作为参数                   前文介绍了如何“csharp通过dll调用opencv函数,图片作为参数”.而在实 ...

  9. Opencv 3.3.0 常用函数

    如何调图像的亮度和对比度? //如何增加图片的对比度或亮度? void contrastOrBrightAdjust(InputArray &src,OutputArray &dst, ...

随机推荐

  1. [ 原创 ]学习笔记-Android 学习笔记 Contacts (一)ContentResolver query 参数详解 [转载]

    此博文转载自:http://blog.csdn.net/wssiqi/article/details/8132603 1.获取联系人姓名 一个简单的例子,这个函数获取设备上所有的联系人ID和联系人NA ...

  2. 第一个ASP.NET MVC应用程序

    首先打开vs2015 文件->新建->项目 选择模版选empty,下面[为下项添加文件夹和核心引用]勾选mvc 点击确定就好

  3. android view surfaceView GLSurfaceView

    韩梦飞沙  韩亚飞  313134555@qq.com  yue31313  han_meng_fei_sha 表面视图 SurfaceView 是 视图 的子类, 刷新界面速度比 视图 块, 因为它 ...

  4. [POI2015]Myjnie

    [POI2015]Myjnie 题目大意: 有\(n(n\le50)\)家洗车店从左往右排成一排,每家店都有一个正整数价格\(d_i\). 有\(m(m\le4000)\)个人要来消费,第\(i\)个 ...

  5. CentOS的利手:“Screen”一个可以在多个进程之间多路复用一个物理终端的窗口管理器

    你是不是经常需要远程登录到Linux服务器?你是不是经常为一些长时间运行的任务头疼?还在用 nohup 吗?那 么来看看 screen 吧,它会给你一个惊喜! 你是不是经常需要 SSH 或者 tele ...

  6. zoj 3469 区间dp **

    题意:有一家快餐店送外卖,现在同时有n个家庭打进电话订购,送货员得以V-1的速度一家一家的运送,但是每一个家庭都有一个不开心的值,每分钟都会增加一倍,值达到一定程度,该家庭将不会再订购外卖了,现在为了 ...

  7. 从数组中查看某值是否存在,Arrays.binarySearch

    Arrays.binarySearch为二分法查询,注意:需要排序 使用示例 Arrays.binarySearch(selectedRows, i) >= 0

  8. 仅100行的JavaScript DOM操作类库

    如果你构建过Web引用程序,你可能处理过很多DOM操作.访问和操作DOM元素几乎是每一个Web应用程序的通用需求.我们我们经常从不同的控件收集信息,我们需要设置value值,修改div或span标签的 ...

  9. angularJS简介及其特点—— 五大特性,加快 Web 应用开发

    AngularJS 是谷歌的一个 JavaScript 框架,旨在简化前端应用程序的开发. 一. 关于和jquery的比较 首先angular是一个mvc框架,它与jquery不同之处在于,前者致力于 ...

  10. Codeforces Round #358 (Div. 2) A. Alyona and Numbers 水题

    A. Alyona and Numbers 题目连接: http://www.codeforces.com/contest/682/problem/A Description After finish ...