我已多次阅读calcHist()的文档,但我认为我对OpenCV的经验不足以及生锈的编程技巧完全阻止我理解它。
我正在考虑计算HSV图像(Hue或channel [0])的一个通道中的像素以进行分割,使用10个接近颜色的区域(根据类似的东西)(让我用这个作为例子,我偷了网络上的范围 - fwiw,省略紫红色似乎是错误的:
红色:0-19& 330-360 红黄色(RY):20-49 黄色:50-69 YG:70-84 格林:85-170 GB:171-191 蓝色:192-264 英国石油公司:265-289 紫色:290-329
等等......
那么我如何使用calcHist做到这一点?
我到目前为止:
#include <opencv2/opencv.hpp>
#include <vector>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main(int argc, char *argv[])
{
Mat scene, sceneHSV, dest, histo;
int numImages = 1, histChannel[] = {0}, dims = 1, histSize[] = {10};
float redRange[] = {0, 10};
float roRange[] = {10, 25};
float orangeRange[] = {25, 35};
float oyRange[] = {35, 42};
float yellowRange[] = {42, 85};
float ygRange[] = {85, 96};
float greenRange[] = {96, 132};
float gbRange[] = {132, 145};
float blueRange[] = {145, 160};
float bpRange[] = {160, 165};
float purpleRange[] = {165, 180};
const float* ranges[] = {redRange, roRange, orangeRange, oyRange, yellowRange, ygRange, greenRange, gbRange, blueRange, bpRange, purpleRange};
vector<Mat> channels;
scene = imread("Apple.jpg", 1);
if (scene.data == NULL)
{
cout<<"FAIL"<<endl;
cin.get();
}
cvtColor(scene, sceneHSV, CV_BGR2HSV);
dilate(sceneHSV, sceneHSV, Mat(), Point(-1, -1), 1, BORDER_CONSTANT, 1);
pyrMeanShiftFiltering(sceneHSV, dest, 2, 50, 3);
split(sceneHSV, channels);
calcHist(&scene, 1, histChannel, Mat(), histo, dims, histSize, ranges, false, false);
cout<<histo<<endl;
waitKey(0);
return 0;
}
现在怎样?在这种情况下,calcHist的参数会是什么样的,输出直方图是什么样的?只是一个完整的1x9阵列?
非常感谢。
答案 0 :(得分:5)
我修改了here
中的代码您可能还想查看cvtColor here
的文档请注意,我没有尝试编译或运行此代码,因此我不保证它会起作用。但是,它可能有用作参考。
Mat hist;
int nimages = 1; // Only 1 image, that is the Mat scene.
int channels[] = {0} // Index for hue channel
int dims = 1 // Only 1 channel, the hue channel
int histSize[] = {9} // 9 bins, 1 each for Red, RY, Yellow, YG etc.
float hranges[] = { 0, 180 }; // hue varies from 0 to 179, see cvtColor
const float *ranges[] = {hranges};
// Compute the histogram.
calcHist(&scene,
nimages,
channels,
Mat(), // No mask
hist, dims, histSize, ranges, uniform=true)
// Now hist will contain the counts in each bin.
// Lets just print out the values. Note that you can output Mat using std::cout
cout << "Histogram: " << endl << hist << endl;
// To access the individual bins, you can either iterate over them
// or use hist.at<uchar>(i, j); Note that one of the index should be 0
// because hist is 1D histogram. Print out hist.rows and hist.cols to see if hist is a N x 1 or 1 x N matrix.
/*
MatIterator_<uchar> it, end;
int binIndex = 0;
for( it = hist.begin<uchar>(), end = hist.end<uchar>(); it != end; ++it)
{
printf("Count in %d bin: %d\n", binIndex, *it);
++binIndex;
}
*/