不同範圍灰階直方圖
#include <cv.h>
#include <highgui.h>
#include <stdio.h>
int HistogramBins = 50;
int HistogramBinWidth;
float HistogramRange1[2]={0,255};
float *HistogramRange[1]={
&
HistogramRange1[0]};float MinValue,MaxValue;
int MinIndex,MaxIndex;
int main()
{
IplImage *Image1;
CvHistogram *Histogram1;
IplImage *HistogramImage1;
IplImage *HistogramImage2;
CvPoint Point1;
CvPoint Point2;
Image1=cvLoadImage("Riverbank.jpg",0);
Histogram1 = cvCreateHist(1,
&
HistogramBins,CV_HIST_ARRAY,HistogramRange);HistogramImage1 = cvCreateImage(cvSize(256,300),8,3);
HistogramImage2 = cvCreateImage(cvSize(256,300),8,3);
cvSetZero(HistogramImage1);
HistogramImage1->origin=1;
HistogramImage2->origin=1;
HistogramBinWidth=256/HistogramBins;
cvCalcHist(
&
Image1,Histogram1);cvNormalizeHist(Histogram1,5000);
cvGetMinMaxHistValue(Histogram1,
&
MinValue,&
MaxValue,&
MinIndex,&
MaxIndex);printf("Histogram1\n");
printf("The Minimum value : %f\tIndex :%d\n",MinValue,MinIndex);
printf("The Maximum value : %f\tIndex :%d\n",MaxValue,MaxIndex);
for(int i=0;i<HistogramBins;i++)
{
Point1=cvPoint(i*HistogramBinWidth,0);
Point2=cvPoint((i+1)*HistogramBinWidth,(int)cvQueryHistValue_1D(Histogram1,i));
cvRectangle(HistogramImage1,Point1,Point2,CV_RGB(127,127,127));
}
cvClearHist(Histogram1);
HistogramRange1[0]=30;
HistogramRange1[1]=255;
HistogramRange[0]=
&
HistogramRange1[0];cvSetHistBinRanges(Histogram1,HistogramRange);
cvCalcHist(
&
Image1,Histogram1);cvNormalizeHist(Histogram1,5000);
cvGetMinMaxHistValue(Histogram1,
&
MinValue,&
MaxValue,&
MinIndex,&
MaxIndex);printf("\nHistogram2\n");
printf("The Minimum value : %f\tIndex :%d\n",MinValue,MinIndex);
printf("The Maximum value : %f\tIndex :%d\n",MaxValue,MaxIndex);
for(int i=0;i<HistogramBins;i++)
{
Point1=cvPoint(i*HistogramBinWidth,0);
Point2=cvPoint((i+1)*HistogramBinWidth,(int)cvQueryHistValue_1D(Histogram1,i));
cvRectangle(HistogramImage2,Point1,Point2,CV_RGB(127,127,127));
}
cvReleaseHist(
&
Histogram1);cvNamedWindow("Histogram1",1);
cvNamedWindow("Histogram2",1);
cvNamedWindow("Riverbank",1);
cvShowImage("Riverbank",Image1);
cvShowImage("Histogram1",HistogramImage1);
cvShowImage("Histogram2",HistogramImage2);
cvWaitKey(0);
}
執行結果:
這個執行出來得結果可以看得出來,直方圖的範圍改變之後,長方形的數據有向右平移的樣子,而在之前的前面的程式碼cvQueryHistValue_1D()所直接輸出的數據實在是過大了,在繪製直方圖的時候一定會超出座標軸的範圍,所以就在前面的程式碼以全部除以50來代替,這邊,改用另外一個解決的方法,cvNormalizeHist(),這個函數是將直方圖所有區塊加起來會等於5000,也就是直方圖數據的總和會等於5000,因此,用這種量化的方式可以避免直方圖因為數據過大而圖形繪不出來的問題,近而縮小直方圖所有的數據,當然,這樣的結果直方圖數據會變成相對的,而cvNormalizeHist()內部則是使用到了cvScale()這個函式來計算,cvGetMinMaxHistValue(),則是找出直方圖的最大值跟最小值的方法,跟前面的最大最小值不太一樣的地方,這邊找出了直方圖的最大值將會代表的是眾數,在統計上是很具意義的東西,cvGetMinMaxHistValue()同樣內部使用的是cvMinMaxLoc()的函式.再來的部分就是用cvClearHist()清除直方圖資料,從新設定直方圖的範圍為30~255,使用cvSetHistBinRanges()的函數,最後再用cvReleaseHist()釋放CvHistogram的記憶體
接下來的這個的結果也是有趣,它可以將直方圖較小的區塊去除掉,這個函式在可以用來製作去除最小面積的圖形區塊,當然在這前面就必須要建立一些相關的演算法來建構直方圖,這邊就簡單介紹cvThreshHist()的操作
去除較小直方圖區塊
#include <cv.h>
#include <highgui.h>
#include <stdio.h>
int HistogramBins = 50;
int HistogramBinWidth;
float HistogramRange1[2]={0,255};
float *HistogramRange[1]={
&
HistogramRange1[0]};float MinValue,MaxValue;
int MinIndex,MaxIndex;
int main()
{
IplImage *Image1;
CvHistogram *Histogram1;
CvHistogram *Histogram2;
IplImage *HistogramImage1;
IplImage *HistogramImage2;
CvPoint Point1;
CvPoint Point2;
Image1=cvLoadImage("Riverbank.jpg",0);
Histogram1 = cvCreateHist(1,
&
HistogramBins,CV_HIST_ARRAY,HistogramRange);HistogramImage1 = cvCreateImage(cvSize(256,300),8,3);
HistogramImage2 = cvCreateImage(cvSize(256,300),8,3);
cvSetZero(HistogramImage1);
HistogramImage1->origin=1;
HistogramImage2->origin=1;
HistogramBinWidth=256/HistogramBins;
cvCalcHist(
&
Image1,Histogram1);cvNormalizeHist(Histogram1,5000);
for(int i=0;i<HistogramBins;i++)
{
Point1=cvPoint(i*HistogramBinWidth,0);
Point2=cvPoint((i+1)*HistogramBinWidth,(int)cvQueryHistValue_1D(Histogram1,i));
cvRectangle(HistogramImage1,Point1,Point2,CV_RGB(127,127,127));
}
Histogram2 = cvCreateHist(1,
&
HistogramBins,CV_HIST_ARRAY,HistogramRange);cvCopyHist(Histogram1,
&
Histogram2);cvThreshHist(Histogram2,50);
for(int i=0;i<HistogramBins;i++)
{
Point1=cvPoint(i*HistogramBinWidth,0);
Point2=cvPoint((i+1)*HistogramBinWidth,(int)cvQueryHistValue_1D(Histogram2,i));
cvRectangle(HistogramImage2,Point1,Point2,CV_RGB(127,127,127));
}
cvReleaseHist(
&
Histogram1);cvReleaseHist(
&
Histogram2);cvNamedWindow("Histogram1",1);
cvNamedWindow("Histogram2",1);
cvNamedWindow("Riverbank",1);
cvShowImage("Riverbank",Image1);
cvShowImage("Histogram1",HistogramImage1);
cvShowImage("Histogram2",HistogramImage2);
cvWaitKey(0);
}
執行結果:
在這邊同樣建立了一個50個區塊,範圍為0~255的直方圖,這裡開啟了兩個CvHistogram的資料結構,並且初始化用cvCopyHist()複製直方圖裡面的資料,而第二個直方圖資料結構Histogram2則是給定一個區塊門檻值,也就是當小於50的區塊數據就會被剃掉,因此圖形顯示的結果,小於50數據的直方圖都被刪除了.
cvNormalizeHist()
將所有直方圖的數據標準化,也就是將所有數據總和為指定的一個數,第一個引數為輸入CvHistogram資料結構,第二個引數為輸入double型別指定總和數據,cvNormalizeHist()內部使用cvScale()函式
cvNormalizeHist(輸入CvHistogram資料結構,輸入double型別總和數據)
cvGetMinMaxHistValue()
取得直方圖的最大最小值的數據,以及它得位置(Index),對於灰階統計直方圖,可以知道是哪個色彩數據擁有最大值,第一個引數為輸入CvHistogram資料結構,第二個引數為輸出float型別最小值數據,第三個引數為輸出float型別最大值數據,第四個引數為輸出int型別最小值的陣列索引(Index),第五個引數為輸出int型別最大值的陣列索引(Index)
cvGetMinMaxHistValue(輸入CvHistogram資料結構,輸出float最小值數據,輸出float最大值數據,輸出int最小值索引,輸出int最大值索引)
cvClearHist()
清除目標CvHistogram直方圖資料結構內的資料.
cvClearHist(目標CvHistogram資料結構)
cvSetHistBinRanges()
從新設立直方圖的數據範圍,也就是要挑選的直方圖最小值下限以及最大值上限,第一個引數為輸入CvHistogram資料結構,第二個引數為輸入float型別的範圍二維陣列
cvSetHistBinRanges(輸入CvHistogram資料結構,輸入float型別範圍二維陣列)
cvReleaseHist()
釋放CvHistogram直方圖資料結構記憶體位址
cvReleaseHist(目標CvHistogram直方圖資料結構)
cvCopyHist()
複製目標CvHistogram資料結構,包括設定直以及直方圖數據資料,第一個引數為輸入目標CvHistogram資料結構直方圖,第二個引數為輸出CvHistogram資料結構直方圖
cvCopyHist(輸入CvHistogram資料結構,輸出要被複製的CvHistogram資料結構)
cvThreshHist()
去除小於目標數據的直方圖區塊,第一個引數為輸入CvHistogram直方圖資料結構,第二個引數為輸入double型別要被刪除的直方圖區塊數據大小
cvThreshHist(輸入CvHistogram資料結構,輸入小於門檻值double型別的數據)
1 意見:
#include
#include
int main( int argc, char** argv )
{
IplImage* src[4];
int i,j,k;
//if( argc >= 5)
src[0] = cvLoadImage("HandIndoorColor.jpg",1);
src[1] = cvLoadImage("HandIndoorColor.jpg",1);
src[2] = cvLoadImage("HandOutdoorColor.jpg",1);
src[3] = cvLoadImage("HandOutdoorSunColor.jpg",1);
// Compute the HSV image, and decompose it into separate planes.
//
IplImage *hsv[4], *y_plane[4],*s_plane[4],*v_plane[4],*planes[4][3];
CvHistogram* hist[4];
IplImage* histimg[4];
int y_bins = 256, s_bins = 256, v_bins= 256;
int hist_size[] = { y_bins };
float h_ranges[2] = { 0, 255 };
//float s_ranges[2] = { 0, 255 };
//float v_ranges[2] = { 0, 255 };
float* ranges[1] = { h_ranges };
int bin_w;
float max_val;
for(i=0; i<=3; i++)
{
hsv[i] = cvCreateImage( cvGetSize(src[i]), 8, 3 );
cvCvtColor( src[i], hsv[i], CV_BGR2YCrCb );
y_plane[i] = cvCreateImage( cvGetSize(src[i]), 8, 1 );
s_plane[i] = cvCreateImage( cvGetSize(src[i]), 8, 1 );
v_plane[i] = cvCreateImage( cvGetSize(src[i]), 8, 1 );
planes[i][0] = y_plane[i];
planes[i][1] = s_plane[i];
planes[i][2] = v_plane[i];
cvCvtPixToPlane( hsv[i], y_plane[i], s_plane[i], v_plane[i], 0 );
// Build the histogram and compute its contents.
hist[i] = cvCreateHist( 1, hist_size, CV_HIST_ARRAY, ranges, 1 );
cvCalcHist( &y_plane[i], hist[i], 0, 0 );
//cvNormalizeHist( hist[i], 1.0 );
histimg[i] = cvCreateImage( cvSize(320,200), 8, 3 );
cvZero( histimg[i] );
cvGetMinMaxHistValue( hist[i], 0, &max_val, 0, 0 );
cvConvertScale( hist[i]->bins, hist[i]->bins, max_val?255.00f/max_val:0.00f, 0 ); // 坫溫 bin 善潔 [0,360]
cvZero( histimg[i] );
bin_w = histimg[i]->width / y_bins;
for( k = 0; k < y_bins; k++ )
{
double val = ( cvGetReal1D(hist[i]->bins,k) * histimg[i]->height/256.00f );
CvScalar color = CV_RGB(255,0,0);
cvRectangle(histimg[i],
cvPoint(k*bin_w,histimg[i]->height),
cvPoint((k+1)*bin_w,(int)(histimg[i]->height - val)),
color,
1,
8,
0 );
}
}//For the 5 images
for(i=0; i<=3; ++i)
cvNormalizeHist( hist[i], 1.00f );
for(i=1; i<=3; ++i)
{//For histogram
printf("Map0 : Map%d\n",i);
for(j=0; j<=3; j++)
{
printf("Method %d ",j);
printf("%lf",cvCompareHist(hist[0],hist[i],j));
printf("\n");
}
printf("\n");
}
cvNamedWindow( "Histogram 0", 0 );
cvShowImage( "Histogram 0", histimg[0] );
cvNamedWindow( "Histogram 1", 0 );
cvShowImage( "Histogram 1", histimg[1] );
cvNamedWindow( "Histogram 2", 0 );
cvShowImage( "Histogram 2", histimg[2] );
cvNamedWindow( "Histogram 3", 0 );
cvShowImage( "Histogram 3", histimg[3] );
cvWaitKey(0);
}
//Jesse Stone Taiwan
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