利用OpenCV画HSV的3D直方图

此代码是根据opencv附带例子修改而成。

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#include <iostream>

#include <time.h>

#include <cv.h>

#include <highgui.h>

#include <math.h>

#include "CommandParser.h"

using namespace std;

int main(int argc, char** argv)

{

void WrongUsage();

CommandParser cp(argc,argv); // object to parse command line

double total_time =0;

double score= 0.8;

//Load Template image

char *param;

char * filename;

filename=param = cp.GetParameter("-i");

if(param==NULL)

{

cout<<"ERROR: Template image argument missing";

WrongUsage();

return -1;

}

IplImage * src= cvLoadImage(param);

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

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 ,v_plane};

/** H 分量划分为16个等级，S分量划分为8个等级 */

int h_bins = 10, s_bins = 6,v_bins = 6;

param = cp.GetParameter("-h");

if(param)

{

h_bins=atoi(param);

}

param = cp.GetParameter("-s");

if(param)

{

s_bins=atoi(param);

}

param = cp.GetParameter("-v");

if(param)

{

v_bins=atoi(param);

}

int hist_size[] = {h_bins, s_bins,v_bins};

/** H 分量的变化范围 */

float h_ranges[] = { 0, 180 };

/** S 分量的变化范围*/

float s_ranges[] = { 0, 255 };

float v_ranges[] = { 0, 255 };

float* ranges[] = { h_ranges, s_ranges,v_ranges };

/** 输入图像转换到HSV颜色空间 */

cvCvtColor( src, hsv, CV_BGR2HSV );

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

/** 创建直方图，二维, 每个维度上均分 */

CvHistogram * hist = cvCreateHist(3, hist_size, CV_HIST_ARRAY, ranges, 1 );

/** 根据H,S两个平面数据统计直方图 */

cvCalcHist( planes, hist, 0, 0 );

/** 获取直方图统计的最大值，用于动态显示直方图 */

float max_value;

int maxid[4]={0};

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

/** 设置直方图显示图像 */

int height = 520;

int ivh=height/v_bins;

int width = (h_bins*s_bins*6);//每个bin6像素

IplImage* hist_img = cvCreateImage( cvSize(width,height), 8, 3 );

cvZero( hist_img );

CvFont font = cvFont(1,1);

/** 用来进行HSV到RGB颜色转换的临时单位图像 */

IplImage * hsv_color = cvCreateImage(cvSize(1,1),8,3);

IplImage * rgb_color = cvCreateImage(cvSize(1,1),8,3);

int bin_w = width / (h_bins * s_bins);

char dspStr1[80];

sprintf(dspStr1,"max=%f",max_value);

cvPutText(hist_img,dspStr1,cvPoint(20,20),&font,cvScalar(0,0xff));

cout<< dspStr1 <<endl;

float tatal_val=0;

bool bh=false;

float htotal=0.0;

for(int v=0;v<v_bins;v++)

{

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

{

bh=false;

float hto=0.0;

int i=0;

for(int s = 0; s < s_bins; s++)

{

i = h*s_bins + s;

/** 获得直方图中的统计次数，计算显示在图像中的高度 */

float bin_val = cvQueryHistValue_3D( hist, h, s,v );

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

tatal_val+=bin_val;

hto+=bin_val;

if(bin_val==max_value)

{

bh=true;

sprintf(dspStr1,"h=%d,s=%d,v=%d",h,s,v);

cvPutText(hist_img,dspStr1,cvPoint(20,50),&font,cvScalar(0xff,0xaf));

cout<< dspStr1 <<endl;

}

/** 获得当前直方图代表的颜色，转换成RGB用于绘制 */

float vhr=(v+0.5)*255.f/v_bins;//避免显示黑色

cvSet2D(hsv_color,0,0,cvScalar(h*180.f / h_bins,(s+0.5)*255.f/s_bins,vhr,0));

cvCvtColor(hsv_color,rgb_color,CV_HSV2BGR);

CvScalar color = cvGet2D(rgb_color,0,0);

cvRectangle( hist_img, cvPoint(i*bin_w,(v+1)*ivh),

cvPoint((i+1)*bin_w,(v+1)*ivh - intensity),

color, -1, 8, 0 );

}

if(bh)

{

htotal=hto;

}

cvLine(hist_img,cvPoint((i+1)*bin_w,v*ivh),cvPoint((i+1)*bin_w,(v+1)*ivh),cvScalar(0xA,0xff,0x98));

}

cvLine(hist_img,cvPoint(0,(v+1)*ivh),cvPoint(width,(v+1)*ivh),cvScalar(0xA,0xff,0x98));

}

sprintf(dspStr1,"pixels=%f",tatal_val);

cvPutText(hist_img,dspStr1,cvPoint(20,80),&font,cvScalar(0,0xff));

cout<< dspStr1 <<endl;

sprintf(dspStr1,"rate=%f",htotal/tatal_val);

cvPutText(hist_img,dspStr1,cvPoint(20,110),&font,cvScalar(0,0xff,0xff));

cout<< dspStr1 <<endl;

sprintf(dspStr1,"maxrt=%f",max_value/tatal_val);

cvPutText(hist_img,dspStr1,cvPoint(20,140),&font,cvScalar(0xff,0xaf));

cout<< dspStr1 <<endl;

cvNamedWindow(filename, 1 );

cvShowImage( filename, src );

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

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

cvWaitKey(0);

}

代码效果如下：

原图



3D 直方图



图上表明最大像素数的HSV的值，以及该值所占比率。

转自：http://blog.csdn.net/foolpanda1168/article/details/6078463