calchist函數(shù)需要包含頭文件

#include <opencv2/imgproc/imgproc.hpp>

函數(shù)聲明(三個重載 calchist函數(shù))：

//! computes the joint dense histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,const int* channels, InputArray mask,OutputArray hist, int dims, const int* histSize,const float** ranges, bool uniform=true, bool accumulate=false );//! computes the joint sparse histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,const int* channels, InputArray mask,SparseMat& hist, int dims,const int* histSize, const float** ranges,bool uniform=true, bool accumulate=false );CV_EXPORTS_W void calcHist( InputArrayOfArrays images,const vector<int>& channels,InputArray mask, OutputArray hist,const vector<int>& histSize,const vector<float>& ranges,bool accumulate=false );

官方文檔：

The functions?calcHist?calculate the histogram of one or more arrays. The elements of a tuple used to increment a histogram bin are taken from the corresponding input arrays at the same location. The sample below shows how to compute a 2D Hue-Saturation histogram for a color image.

Parameters:

images?– Source arrays. They all should have the same depth,?CV_8U?or?CV_32F?, and the same size. Each of them can have an arbitrary number of channels. nimages?– Number of source images. channels?– List of the?dims?channels used to compute the histogram. The first array channels are numerated from 0 to?images[0].channels()-1?, the second array channels are counted from?images[0].channels()?to?images[0].channels()?+?images[1].channels()-1, and so on. mask?– Optional mask. If the matrix is not empty, it must be an 8-bit array of the same size as?images[i]?. The non-zero mask elements mark the array elements counted in the histogram. hist?– Output histogram, which is a dense or sparse?dims?-dimensional array. dims?– Histogram dimensionality that must be positive and not greater than?CV_MAX_DIMS?(equal to 32 in the current OpenCV version). histSize?– Array of histogram sizes in each dimension. ranges?– Array of the?dims?arrays of the histogram bin boundaries in each dimension. When the histogram is uniform (?uniform?=true), then for each dimension?i?it is enough to specify the lower (inclusive) boundary??of the 0-th histogram bin and the upper (exclusive) boundary??for the last histogram bin?histSize[i]-1?. That is, in case of a uniform histogram each of?ranges[i]?is an array of 2 elements. When the histogram is not uniform (?uniform=false?), then each of?ranges[i]?contains?histSize[i]+1?elements:?. The array elements, that are not between??and??, are not counted in the histogram. uniform?– Flag indicating whether the histogram is uniform or not (see above). accumulate?– Accumulation flag. If it is set, the histogram is not cleared in the beginning when it is allocated. This feature enables you to compute a single histogram from several sets of arrays, or to update the histogram in time.

釋義：

images：源圖像矩陣(可以多個，但必須滿足一定條件：同等深度，同等大小，同種數(shù)據(jù)類型：CV_8U或CV_32F，通道數(shù)不需要一致)

nimages：源圖像個數(shù)

channels：用來計算直方圖

例程：

#include <cv.h>
#include <highgui.h>using namespace cv;int main( int argc, char** argv )
{Mat src, hsv;if( argc != 2 || !(src=imread(argv[1], 1)).data )return -1;cvtColor(src, hsv, CV_BGR2HSV);// Quantize the hue to 30 levels// and the saturation to 32 levelsint hbins = 30, sbins = 32;int histSize[] = {hbins, sbins};// hue varies from 0 to 179, see cvtColorfloat hranges[] = { 0, 180 };// saturation varies from 0 (black-gray-white) to// 255 (pure spectrum color)float sranges[] = { 0, 256 };const float* ranges[] = { hranges, sranges };MatND hist;// we compute the histogram from the 0-th and 1-st channelsint channels[] = {0, 1};calcHist( &hsv, 1, channels, Mat(), // do not use maskhist, 2, histSize, ranges,true, // the histogram is uniformfalse );double maxVal=0;minMaxLoc(hist, 0, &maxVal, 0, 0);int scale = 10;Mat histImg = Mat::zeros(sbins*scale, hbins*10, CV_8UC3);for( int h = 0; h < hbins; h++ )for( int s = 0; s < sbins; s++ ){float binVal = hist.at<float>(h, s);int intensity = cvRound(binVal*255/maxVal);rectangle( histImg, Point(h*scale, s*scale),Point( (h+1)*scale - 1, (s+1)*scale - 1),Scalar::all(intensity),CV_FILLED );}namedWindow( "Source", 1 );imshow( "Source", src );namedWindow( "H-S Histogram", 1 );imshow( "H-S Histogram", histImg );waitKey();
}

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轉(zhuǎn)載于:https://www.cnblogs.com/Atanisi/p/6910125.html

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