wanglang3081的专栏

In this tutorial you will learn how to:Load an image (using imread)Create a named OpenCV window (using namedWindow)Display an image in an OpenCV window (using imshow)#include #inc

Discriminatively Trained Part Based Models for Object DetectionThe object detector described below has been initially proposed byP.F. Felzenszwalb in[Felzenszwalb2010]. It is based on aDalal-Tri

ExamplesSmall imageThe following is the same 8x8 subimage as used in JPEG. The 8-bit greyscale image shown has the following values:The histogram for this image is shown in the following tab

GoalIn this tutorial you will learn how to:Use the OpenCV functions CvSVM::train to build a classifier based on SVMs and CvSVM::predict to test its performance.What is a SVM?A Su

In this tutorial you will learn how to:Apply two very common morphology operators: Dilation and Erosion. For this purpose, you will use the following OpenCV functions:erodedilateCool The

GoalIn this tutorial you will learn how to:Use the OpenCV function morphologyEx to apply Morphological Transformation such as:OpeningClosingMorphological GradientTop HatBlack Hat

GoalIn this tutorial you will learn how to:Use the OpenCV function Canny to implement the Canny Edge Detector.TheoryThe Canny Edge detector was developed by John F. Canny in 1986

GoalIn this tutorial you will learn how to:Use the OpenCV function Laplacian to implement a discrete analog of the Laplacian operator.TheoryIn the previous tutorial we learned

GoalIn this tutorial you will learn how to:Define the optimization problem for SVMs when it is not possible to separate linearly the training data.How to configure the parameters in CvSVMPar

GoalIn this tutorial you will learn how to:Use the OpenCV function split to divide an image into its correspondent planes.To calculate histograms of arrays of images by using the OpenCV func

The Haar basisThe Haar wavelet is defined as:The Haar basis, consisting of the functionsthat is rescaled versions of (by) shifted by.These functions are orthogonal i.e.Moreover, the

An Introduction to Wavelets and the Haar Transformby Musawir Ali In this article, I will present an introduction to “wavelets” and the 1D Haar Transform. Then I will show how the 1D Haar T

用OpenCV做算法的朋友们肯定为随机数烦恼过，新版本一直支持随机数产生器啦，而且还继续支持之前版本的c格式的函数，不过与时俱进，我这里介绍C++的RNG类。它可以压缩一个64位的i整数并可以得到scalar和array的随机数。目前的版本支持均匀分布随机数和Gaussian分布随机数。随机数的产生采用的是Multiply-With-Carry算法和Ziggurat算法。其构造函数的初始化可以

IntroductionThe work with a cascade classifier inlcudes two major stages: training and detection.Detection stage is described in a documentation ofobjdetect module of general OpenCV documentation.

使用OPENCV训练手写数字识别分类器 1，下载训练数据和测试数据文件，这里用的是MNIST手写数字图片库，其中训练数据库中为60000个，测试数据库中为10000个2，创建训练数据和测试数据文件读取函数，注意字节顺序为大端3，确定字符特征方式为最简单的8×8网格内的字符点数4，创建SVM，训练并读取，结果如下 1000个训练样本，测试数据正确率80.21%（并没有体现SV

OpenCV在新版本中把很多C语言的代码都重新整理成了C++代码，让我们在使用的时候更加方便灵活。其中对于特征点的提取和匹配，充分体现了C++的强大。下面直接用例子来说明。假设我们有两幅图：1.bmp和2.bmp，要从中提取体征点并匹配，代码如下： // Load image from fileIplImage *pLeftImage = cvLoadImage("1.bmp",CV_

http://docs.opencv.org/doc/tutorials/imgproc/histograms/back_projection/back_projection.html?highlight=normalizehttp://docs.opencv.org/modules/core/doc/operations_on_arrays.html?highlight=normalize#

What is an Image Histogram?It is a graphical representation of the intensity distribution of an image.It quantifies the number of pixels for each intensity value considered.What is Histo

In this tutorial you will learn how to:Load an image using imreadTransform an image from BGR to Grayscale format by usingcvtColorSave your transformed image in a file on disk (usingimw

he first thing you need to be familiar with is how OpenCV stores and handles images.MatC interface  store the image in the memory  used a C structure calledIplImage.  (openCV 1.x)The p

Create your own c++ opencv xcode projectfire up xcode and create a new xcode projectselect Command Line Tool for the type of project under os xopen your project's build settingsunder Architectures

一、安装OpenCV for MAC 1.     首先下载opencv for mac安装源文件，解压缩2.     安装cmake程序。笔者使用的是Homebrew，在终端中输入：“brew install cmake”，自动安装cmake。3.     进入存放解压后的opencv文件夹，新建一个空的文件夹release，进入该文件夹，编译安装opencv，使用命令如下：

GoalWe’ll seek answers for the following questions:How to go through each and every pixel of an image?How is OpenCV matrix values stored?How to measure the performance of our algorithm?What ar

http://docs.opencv.org/trunk/modules/imgproc/doc/miscellaneous_transformations.html?highlight=cvtcolor#void%20cvtColor%28InputArray%20src,%20OutputArray%20dst,%20int%20code,%20int%20dstCn%29cvtCol

GoalIn this chapterWe will revisit the hand-written data OCR, but, with SVM instead of kNN.OCR of Hand-written DigitsIn kNN, we directly used pixel intensity as the feature vecto

GoalIn this tutorial you will learn how to:Define the optimization problem for SVMs when it is not possible to separate linearly the training data.How to configure the parameters in CvSVMPar

边缘边缘(edge)是指图像局部强度变化最显著的部分。主要存在于目标与目标、目标与背景、区域与区域(包括不同色彩)之间，是图像分割、纹理特征和形状特征等图像分析的重要基础。图像强度的显著变化可分为：阶跃变化函数，即图像强度在不连续处的两边的像素灰度值有着显著的差异；线条（屋顶）变化函数，即图像强度突然从一个值变化到另一个值，保持一较小行程后又回到原来的值。图像的边缘有方向和幅度

GoalIn this tutorial you will learn how to:Use the OpenCV function momentsUse the OpenCV function contourAreaUse the OpenCV function arcLengthTheoryCodeThis tutorial code

// DWT.cpp : 定义控制台应用程序的入口点。//#include "stdafx.h"#include "cv.h"#include "highgui.h"// 二维离散小波变换（单通道浮点图像）void DWT(IplImage *pImage, int nLayer){// 执行条件if (pImage){if (pImage->nChan

这是《小波变换和motion信号处理》系列的第一篇，基础普及。第二篇我准备写深入小波的东西，第三篇讲解应用。记得我还在大四的时候，在申请出国和保研中犹豫了好一阵，骨子里的保守最后让我选择了先保研。当然后来也退学了，不过这是后话。当时保研就要找老板，实验室，自己运气还不错，进了一个在本校很牛逼的实验室干活路。我们实验室主要是搞图像的，实力在全国也是很强的，进去后和师兄师姐聊，大家都在搞什么小波变

从前两篇发布到现在，过去一年多了。当初承诺的主要讲解应用的第三篇迟迟没能出炉的原因主要是这个方法用到了我们组的一篇论文中，所以在论文发表之前，不大方便发出来。倒不是说这个方法有多原创创新，只是这是团队工作，我单独提前发出来不大好。现在这篇论文已经录取发表，所以可以不用顾虑放上来了。我本来想讲的东西都在论文中，我也比较懒，就不再翻译一遍了。各位感兴趣的可以从这里下载。因为篇幅原因，和小波相关的文

http://cn.mathworks.com/examples/matlab-computer-vision/732-face-detection-and-tracking-using-the-klt-algorithmThis example shows how to automatically detect and track a face using feature points.