CalcHist

opencv提供了calcHist函式來計算圖像直方圖。

基本介紹

• 中文名：CalcHist
• 類型：函式
• 內容：直方圖
• 特點：多個圖像計算一個單獨的直方圖

opencv函式

image(s) 的直方圖

對於1.0版本：void cvCalcHist( IplImage** image, CvHistogram* hist, int accumulate=0, const CvArr* mask=NULL );

對於2.0版本：

void calcHist(const Mat* arrays, int narrays, const int* channels, InputArray mask, OutputArray
hist, int dims, const int* histSize, const float** ranges, bool uniform=true, bool accumulate=
false )；

void calcHist(const Mat* arrays, int narrays, const int* channels, InputArray mask, SparseMat&
hist, int dims, const int* histSize, const float** ranges, bool uniform=true, bool accumulate=
false )；

image

輸入圖像s (雖然也可以使用 CvMat** ).

hist

直方圖指針

accumulate

累計標識。如果設定，則直方圖在開始時不被清零。這個特徵保證可以為多個圖像計算一個單獨的直方圖，或者線上更新直方圖。

mask

操作 mask, 確定輸入圖像的哪個象素被計數

函式 cvCalcHist 計算一張或多張單通道圖像的直方圖（譯者註：若要計算多通道，可像以下例子那樣用多個單通道圖來表示）。 用來增加直方塊的數組元素可從相應輸入圖像的同樣位置提取。 Sample. 計算和顯示彩色圖像的 2D 色調－飽和度圖像

#include <cv.h>

#include <highgui.h>

int main( int argc, char** argv )

{

IplImage* src;

if( argc == 2 && (src=cvLoadImage(argv[1], 1))!= 0)

{

IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 );

IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 );

IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 );

IplImage* planes[] = { h_plane, s_plane };

IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 );

int h_bins = 30, s_bins = 32; int hist_size[] = {h_bins, s_bins};

/* hue varies from 0 (~0°red) to 180 (~360°red again) */

float h_ranges[] = { 0, 180 };

/* saturation varies from 0 (black-gray-white) to 255 (pure spectrum color) */

float s_ranges[] = { 0, 255 }; float* ranges[] = { h_ranges, s_ranges }; int scale = 10;

IplImage* hist_img = cvCreateImage( cvSize(h_bins*scale,s_bins*scale), 8, 3 );

CvHistogram* hist;

float max_value = 0;

int h, s;

cvCvtColor( src, hsv, CV_BGR2HSV );

cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 );

hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 );

cvCalcHist( planes, hist, 0, 0 );

cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 );

cvZero( hist_img );

for( h = 0; h < h_bins; h++ )

{

for( s = 0; s < s_bins; s++ ) { float bin_val = cvQueryHistValue_2D( hist, h, s );

int intensity = cvRound(bin_val*255/max_value);

cvRectangle( hist_img, cvPoint( h*scale, s*scale ), cvPoint( (h+1)*scale - 1, (s+1)*scale - 1), CV_RGB(intensity,intensity,intensity),

/* graw a grayscale histogram. if you have idea how to do it nicer let us know */

CV_FILLED );

}

}

cvNamedWindow( "Source", 1 );

cvShowImage( "Source", src );

cvNamedWindow( "H-S Histogram", 1 );

cvShowImage( "H-S Histogram", hist_img ); cvWaitKey(0);

cvReleaseImage(&src);

cvReleaseImage(&hist_img);

cvDestroyAllWindows();

}

return 0;

}