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i have come out with a code which able to plot a histogram for an image.
but the image first has to be converted into grayscale.
Does anyone know how can i plot a histogram directly with the RGB value obtain from the image. ? without convert the image into grayscale.
because when directly getting RGB value from an image, basically we will obtain 3 layer of values, thus mostly need 3 histogram to represent each, R , G and B.
is there any method that allow me to plot in 1 histogram ?
thank you so much.
int i, hist_size = 256;
float max_value,min_value;
float min_idx,max_idx;
float bin_w;
float mean =0, variance =0;
float range_0[]={0,256};
float *ranges[]={range_0};
IplImage* im = cvLoadImage("papaya.jpg");
//Create a single planed image of the same size as the original
IplImage* grayImage = cvCreateImage(cvSize(im->width,im->height),IPL_DEPTH_8U, 1);
//convert the original image to gray
cvCvtColor(im, grayImage, CV_BGR2GRAY);
//create a rectangular area to evaluate
CvRect rect = cvRect(0, 0, 500, 600 );
//apply the rectangle to the image and establish a region of interest
cvSetImageROI(grayImage, rect);
//create an image to hold the histogram
IplImage* histImage = cvCreateImage(cvSize(320,200), 8, 1);
//create a histogram to store the information from the image
CvHistogram* hist = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
//calculate the histogram and apply to hist
cvCalcHist( &grayImage, hist, 0, NULL );
//grab the min and max values and their indeces
cvGetMinMaxHistValue( hist, &min_value, &max_value, 0, 0);
//scale the bin values so that they will fit in the image representation
cvScale( hist->bins, hist->bins, ((double)histImage->height)/max_value, 0 );
//set all histogram values to 255
cvSet( histImage, cvScalarAll(255), 0 );
//create a factor for scaling along the width
bin_w = cvRound((double)histImage->width/hist_size);
for( i = 0; i < hist_size; i++ ) {
//draw the histogram data onto the histogram image
cvRectangle( histImage, cvPoint(i*bin_w, histImage->height),cvPoint((i+1)*bin_w,histImage->height - cvRound(cvGetReal1D(hist->bins,i))),cvScalarAll(0), -1, 8, 0 );
//get the value at the current histogram bucket
float* bins = cvGetHistValue_1D(hist,i);
//increment the mean value
mean += bins[0];
}
//finish mean calculation
mean /= hist_size;
//go back through now that mean has been calculated in order to calculate variance
for( i = 0; i < hist_size; i++ ) {
float* bins = cvGetHistValue_1D(hist,i);
variance += pow((bins[0] - mean),2);
}
//finish variance calculation
variance /= hist_size;
cvNamedWindow("Original", 0);
cvShowImage("Original", im );
cvNamedWindow("Gray", 0);
cvShowImage("Gray", grayImage );
cvNamedWindow("Histogram", 0);
cvShowImage("Histogram", histImage );
//hold the images until a key is pressed
cvWaitKey(0);
//clean up images
cvReleaseImage(&histImage);
cvReleaseImage(&grayImage);
cvReleaseImage(&im);
//remove windows
cvDestroyWindow("Original");
cvDestroyWindow("Gray");
cvDestroyWindow("Histogram");
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