//------------------ shows histogram values on the graphic----------------------------------
void MainWindow::on_pushButton_clicked()
{
Histogram1D graph;
cv::namedWindow("histogram graph");
cv::imshow("histogram graph", graph.getHistogramImage(image));
}
void case2histogram() {
cv::Mat image=cv::imread( inputImagePath4case1histogram,cv::IMREAD_GRAYSCALE );//open in b&w
alert_win( image );
Histogram1D h;
cv::Mat re= h.getHistogramImage(image);
alert_win( re );
}
//-------------------- equalized the b&w image -------------------------------------------------
//---------------------- shows it's histogram values on a graph --------------------------------
void MainWindow::on_pushButton_6_clicked()
{
Histogram1D equa;
cv::namedWindow("equalized");
cv::namedWindow("equalized histogram");
cv::Mat equalized=equa.equalize(image);
cv::imshow("equalized",equalized);
cv::imshow("equalized histogram",equa.getHistogramImage(equalized));
}
//---------------------------stretches the image on some level---------------------------------------
//--------------------------- and also show it's histogram level on a grahp--------------------------
void MainWindow::on_pushButton_5_clicked()
{
Histogram1D str;
cv::Mat strecthLevel;
cv::namedWindow("stretched");
int x= ui->lineEdit->text().toInt();
cv::Mat strecthed = str.strecth(image,x);
cv::imshow("stretched", strecthed);
cv::imshow("stretched histogram",str.getHistogramImage(strecthed));
}
int main(int argc, char *argv[])
{
QCoreApplication a(argc, argv);
Mat image = imread("D:\\workspace\\pictures\\771413900_m.jpg",0);
Mat thresholded, result;
Histogram1D h;
MatND histo = h.getHistogram(image);
for (int i=0;i<256;i++)
cout << "Value" << i << "=" << histo.at<float>(i) << endl;
imshow("Orginal", image);
imshow("Histogram",h.getHistogramImage(image));
//threshold(image, thresholded,128,255,THRESH_BINARY);
//imshow("Threshold",thresholded);
equalizeHist(image,result);
//Mat stretched = h.stretch(image,100);
//imshow("Stretched",stretched);
imshow("Equalize",result);
imshow("After Equalize Histogram",h.getHistogramImage(result));
waitKey(50000);
return a.exec();
}
//-------------------- tranforms the image to negative---------------------------------------
//-------------------- shows it's histogram values on graphic--------------------------------
void MainWindow::on_pushButton_4_clicked()
{
Histogram1D negative;
//build look up
int dim(256);
cv::Mat lut(1, &dim, CV_8U); // lut is a matrix which is in 1D
for(int i=0; i<256; i++)
{
lut.at<uchar>(i)=255-i; //takes all the values and reverses it
}
cv::Mat negativeResult;
negativeResult=negative.applyLookUp(image,lut);
cv::namedWindow("negative");
cv::imshow("negative",negativeResult);
//negative image histogram
cv::imshow("negative histogram",negative.getHistogramImage(negativeResult));
}
int main()
{
Mat src;
src = imread("box.png");
if( !src.data )
{
cout<<"error";
}
namedWindow("image", CV_WINDOW_AUTOSIZE );
imshow("image", src );
waitKey(0);
// The histogram object
Histogram1D h;
namedWindow("Histogram");
imshow("Histogram",h.getHistogramImage(src));
waitKey(0);
return 1;
}
int main()
{
// Read input image
cv::Mat image= cv::imread("waves.jpg",0);
if (!image.data)
return 0;
// define image ROI
cv::Mat imageROI;
imageROI= image(cv::Rect(216,33,24,30)); // Cloud region
// Display reference patch
cv::namedWindow("Reference");
cv::imshow("Reference",imageROI);
// Find histogram of reference
Histogram1D h;
cv::Mat hist= h.getHistogram(imageROI);
cv::namedWindow("Reference Hist");
cv::imshow("Reference Hist",h.getHistogramImage(imageROI));
// Create the content finder
ContentFinder finder;
// set histogram to be back-projected
finder.setHistogram(hist);
finder.setThreshold(-1.0f);
// Get back-projection
cv::Mat result1;
result1= finder.find(image);
// Create negative image and display result
cv::Mat tmp;
result1.convertTo(tmp,CV_8U,-1.0,255.0);
cv::namedWindow("Backprojection result");
cv::imshow("Backprojection result",tmp);
// Get binary back-projection
finder.setThreshold(0.12f);
result1= finder.find(image);
// Draw a rectangle around the reference area
cv::rectangle(image, cv::Rect(216, 33, 24, 30), cv::Scalar(0, 0, 0));
// Display image
cv::namedWindow("Image");
cv::imshow("Image",image);
// Display result
cv::namedWindow("Detection Result");
cv::imshow("Detection Result",result1);
// Load color image
ColorHistogram hc;
cv::Mat color= cv::imread("waves.jpg");
// extract region of interest
imageROI= color(cv::Rect(0,0,100,45)); // blue sky area
// Get 3D colour histogram (8 bins per channel)
hc.setSize(8); // 8x8x8
cv::Mat shist= hc.getHistogram(imageROI);
// set histogram to be back-projected
finder.setHistogram(shist);
finder.setThreshold(0.05f);
// Get back-projection of color histogram
result1= finder.find(color);
cv::namedWindow("Color Detection Result");
cv::imshow("Color Detection Result",result1);
// Second color image
cv::Mat color2= cv::imread("dog.jpg");
cv::namedWindow("Second Image");
cv::imshow("Second Image",color2);
// Get back-projection of color histogram
cv::Mat result2= finder.find(color2);
cv::namedWindow("Result color (2)");
cv::imshow("Result color (2)",result2);
// Get ab color histogram
hc.setSize(256); // 256x256
cv::Mat colorhist= hc.getabHistogram(imageROI);
// display 2D histogram
colorhist.convertTo(tmp,CV_8U,-1.0,255.0);
cv::namedWindow("ab histogram");
cv::imshow("ab histogram",tmp);
// set histogram to be back-projected
finder.setHistogram(colorhist);
finder.setThreshold(0.05f);
// Convert to Lab space
cv::Mat lab;
cv::cvtColor(color, lab, CV_BGR2Lab);
// Get back-projection of ab histogram
int ch[2]={1,2};
result1= finder.find(lab,0,256.0f,ch);
cv::namedWindow("Result ab (1)");
cv::imshow("Result ab (1)",result1);
// Second colour image
cv::cvtColor(color2, lab, CV_BGR2Lab);
// Get back-projection of ab histogram
result2= finder.find(lab,0,256.0,ch);
cv::namedWindow("Result ab (2)");
cv::imshow("Result ab (2)",result2);
// Draw a rectangle around the reference sky area
cv::rectangle(color,cv::Rect(0,0,100,45),cv::Scalar(0,0,0));
cv::namedWindow("Color Image");
cv::imshow("Color Image",color);
// Get Hue colour histogram
hc.setSize(180); // 180 bins
colorhist= hc.getHueHistogram(imageROI);
// set histogram to be back-projected
finder.setHistogram(colorhist);
// Convert to HSV space
cv::Mat hsv;
cv::cvtColor(color, hsv, CV_BGR2HSV);
// Get back-projection of hue histogram
ch[0]=0;
result1= finder.find(hsv,0.0f,180.0f,ch);
cv::namedWindow("Result Hue (1)");
cv::imshow("Result Hue (1)",result1);
// Second colour image
color2= cv::imread("dog.jpg");
// Convert to HSV space
cv::cvtColor(color2, hsv, CV_BGR2HSV);
// Get back-projection of hue histogram
result2= finder.find(hsv,0.0f,180.0f,ch);
cv::namedWindow("Result Hue (2)");
cv::imshow("Result Hue (2)",result2);
cv::waitKey();
return 0;
}
cv::Mat ImageProcessor::getHistogram(cv::Mat &origImage) {
Histogram1D h;
return h.getHistogramImage(origImage);
}
int main()
{
// Read input image
cv::Mat image= cv::imread("group.jpg",0);
if (!image.data)
return 0;
// Resize by 70% for book printing
cv::resize(image, image, cv::Size(), 0.7, 0.7);
// save grayscale image
cv::imwrite("groupBW.jpg", image);
// Display the image
cv::namedWindow("Image");
cv::imshow("Image",image);
// The histogram object
Histogram1D h;
// Compute the histogram
cv::Mat histo= h.getHistogram(image);
// Loop over each bin
for (int i=0; i<256; i++)
cout << "Value " << i << " = " << histo.at<float>(i) << endl;
// Display a histogram as an image
cv::namedWindow("Histogram");
cv::imshow("Histogram",h.getHistogramImage(image));
// creating a binary image by thresholding at the valley
cv::Mat thresholded; // output binary image
cv::threshold(image,thresholded,
60, // threshold value
255, // value assigned to pixels over threshold value
cv::THRESH_BINARY); // thresholding type
// Display the thresholded image
cv::namedWindow("Binary Image");
cv::imshow("Binary Image",thresholded);
thresholded = 255 - thresholded;
cv::imwrite("binary.bmp",thresholded);
// Equalize the image
cv::Mat eq= h.equalize(image);
// Show the result
cv::namedWindow("Equalized Image");
cv::imshow("Equalized Image",eq);
// Show the new histogram
cv::namedWindow("Equalized Histogram");
cv::imshow("Equalized Histogram",h.getHistogramImage(eq));
// Stretch the image, setting the 1% of pixels at black and 1% at white
cv::Mat str= h.stretch(image,0.01f);
// Show the result
cv::namedWindow("Stretched Image");
cv::imshow("Stretched Image",str);
// Show the new histogram
cv::namedWindow("Stretched Histogram");
cv::imshow("Stretched Histogram",h.getHistogramImage(str));
// Create an image inversion table
int dim(256);
cv::Mat lut(1, // 1 dimension
&dim, // 256 entries
CV_8U); // uchar
// or cv::Mat lut(256,1,CV_8U);
for (int i=0; i<256; i++) {
lut.at<uchar>(i)= 255-i;
}
// Apply lookup and display negative image
cv::namedWindow("Negative image");
cv::imshow("Negative image",h.applyLookUp(image,lut));
cv::waitKey();
return 0;
}
int main_his()
{
// Read input image
cv::Mat image= cv::imread("Koala.jpg",0);
if (!image.data)
return 0;
// Display the image
cv::namedWindow("Image");
cv::imshow("Image",image);
// The histogram object
Histogram1D h;
// Compute the histogram
cv::MatND histo= h.getHistogram(image);
// Loop over each bin
for (int i=0; i<256; i++)
cout << "Value " << i << " = " << histo.at<float>(i) << endl;
// Display a histogram as an image
cv::namedWindow("Histogram");
cv::imshow("Histogram",h.getHistogramImage(image));
// creating a binary image by thresholding at the valley
cv::Mat thresholded;
cv::threshold(image,thresholded,60,255,cv::THRESH_BINARY);
// Display the thresholded image
cv::namedWindow("Binary Image");
cv::imshow("Binary Image",thresholded);
cv::imwrite("binary.bmp",thresholded);
// Equalize the image
cv::Mat eq= h.equalize(image);
// Show the result
cv::namedWindow("Equalized Image");
cv::imshow("Equalized Image",eq);
// Show the new histogram
cv::namedWindow("Equalized Histogram");
cv::imshow("Equalized Histogram",h.getHistogramImage(eq));
// Stretch the image ignoring bins with less than 5 pixels
cv::Mat str= h.stretch(image,5);
// Show the result
cv::namedWindow("Stretched Image");
cv::imshow("Stretched Image",str);
// Show the new histogram
cv::namedWindow("Stretched Histogram");
cv::imshow("Stretched Histogram",h.getHistogramImage(str));
// Create an image inversion table
//uchar lookup[256];
// Create lookup table
int dims[1]={256};
cv::MatND lookup(1,dims,CV_8U);
for (int i=0; i<256; i++) {
lookup.at<uchar>(i)=255-i;
}
// Apply lookup and display negative image
cv::namedWindow("Negative image");
cv::imshow("Negative image",h.applyLookUp(image,lookup));
cv::waitKey();
return 0;
}
