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Create Exercises_11-1-2-5-6-7.cpp
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‎Exercises_11-1-2-5-6-7.cpp

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//Exercises at end of Chapter 11
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// 1、2、5、6 and 7
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#include <opencv2/opencv.hpp>
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#include <iostream>
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using namespace cv;
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using namespace std;
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void help(const char **argv) {
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cout << "\n\n"
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<< "This program solves the Exercises at the end of Chapter 11(without 3、4 and 8)\n"
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<< "Call:\n"
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<< argv[0] << " <path/image_name>\n\n"
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<< "For example: " << argv[0] << " /AverageMaleFace.jpg\n"
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<< endl;
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}
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// Get the coordinates of the points after the rotation
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Point2f getPointAffinedPos(const Point2f src, const Point2f center, double angle)
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{
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Point dst;
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int x = src.x - center.x;
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int y = src.y - center.y;
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dst.x = x * cos(angle) + y * sin(angle) + center.x;
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dst.y = -x * sin(angle) + y * cos(angle) + center.y;
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return dst;
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}
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int main( int argc, const char** argv )
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{
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help(argv);
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if(argc < 2) {
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cout << "\nERROR: You had too few parameters.\n" << endl;
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return -1;
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}
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/************************************************************************/
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/* 1. Find and load a picture of a face where the face is frontal, has eyes open, and
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takes up most or all of the image area. Write code to find the pupils of the eyes. */
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/************************************************************************/
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Mat matFrontFace = imread(argv[1]);
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Mat gray;Mat temp;
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double minPixelValue, maxPixelValue;
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Point minPixelPoint,maxPixelPoint;
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cvtColor(matFrontFace,gray,COLOR_BGR2GRAY);
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// Laplacian pyramid
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pyrDown(gray,temp);
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pyrUp(temp,temp);
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temp = gray - temp;
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// find and circle the result
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minMaxLoc(temp,&minPixelValue,&maxPixelValue,&minPixelPoint,&maxPixelPoint);
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circle(matFrontFace,maxPixelPoint,10,Scalar(255,255,255),2);
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/************************************************************************/
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/* 2. Look at the diagrams of how the log-polar function transforms a square into a
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wavy line.
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a. Draw the log-polar results if the log-polar center point were sitting on one of
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the corners of the square.
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b. What would a circle look like in a log-polar transform if the center point were
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inside the circle and close to the edge?
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c. Draw what the transform would look like if the center point were sitting just
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outside of the circle. */
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/************************************************************************/
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// draw a circle,white on black.
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Mat matLogPolar = Mat(512,512,CV_8U,Scalar(0));
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circle(matLogPolar,Point(256,256),100,Scalar(255),3);
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//a
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logPolar(matLogPolar,temp,Point(0,0),40,INTER_CUBIC);
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//b
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logPolar(matLogPolar,temp,Point(256-101,256),40,INTER_CUBIC);
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//c the result like two rings
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logPolar(matLogPolar,temp,Point(256-101-3,256),40,INTER_CUBIC);
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/************************************************************************/
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/* 5. Load an image, take a perspective transform, and then rotate it. Can this trans‐
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form be done in one step? */
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/************************************************************************/
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Mat matE5_1 = imread(argv[1]);
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Mat matE5_2 = imread(argv[1]);
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double angle = 45;
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//perspective matrix
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Point2f src_vertices[4];
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src_vertices[0] = Point(0, 0);
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src_vertices[1] = Point(matE5_1.cols, 0);
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src_vertices[2] = Point(matE5_1.cols, matE5_1.rows);
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src_vertices[3] = Point(0, matE5_1.rows);
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Point2f dst_vertices[4];
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dst_vertices[0] = Point(100, 0);
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dst_vertices[1] = Point(matE5_1.cols - 100, 0);
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dst_vertices[2] = Point(matE5_1.cols, matE5_1.rows);
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dst_vertices[3] = Point(0, matE5_1.rows);
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Mat perspectiveMatrix = getPerspectiveTransform(src_vertices, dst_vertices);
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//roate matrix
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Mat affineMatrix = getRotationMatrix2D(Point(matE5_1.cols/2,matE5_1.rows/2), angle, 1.0 );
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// perspective -> rotate
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warpPerspective(
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matE5_1,
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matE5_1,
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perspectiveMatrix,
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matE5_1.size(),
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INTER_LINEAR,
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BORDER_CONSTANT,
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Scalar());
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warpAffine(
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matE5_1,
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matE5_1,
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affineMatrix,
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matE5_1.size(),
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INTER_LINEAR,
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BORDER_CONSTANT,
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Scalar()
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);
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// do it in one step
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Point center = Point(matE5_2.cols/2,matE5_2.rows/2);
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dst_vertices[0] = getPointAffinedPos(dst_vertices[0],center,angle);
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dst_vertices[1] = getPointAffinedPos(dst_vertices[1],center,angle);
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dst_vertices[2] = getPointAffinedPos(dst_vertices[2],center,angle);
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dst_vertices[3] = getPointAffinedPos(dst_vertices[3],center,angle);
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perspectiveMatrix = getPerspectiveTransform(src_vertices, dst_vertices);
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warpPerspective(
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matE5_2,
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matE5_2,
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perspectiveMatrix,
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matE5_2.size(),
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INTER_LINEAR,
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BORDER_CONSTANT,
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Scalar());
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// the result is almost the same
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/************************************************************************/
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/* 6. Inpainting works pretty well for the repair of writing over textured regions. What
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would happen if the writing obscured a real object edge in a picture? Try it. */
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/************************************************************************/
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Mat matInpaint = imread(argv[1]);
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Mat matInpaintMask = Mat(matInpaint.size(),CV_8UC1,Scalar(0));//the same size,all in black(oh yeah!)
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//draw the same circle on the matInpaint and matInpaintMask
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circle(matInpaint,Point(255,255),100,Scalar(255),10);
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circle(matInpaintMask,Point(255,255),100,Scalar(255),10);
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imshow("befor inpaint",matInpaint);
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inpaint(matInpaint,matInpaintMask,matInpaint,10,CV_INPAINT_TELEA);
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imshow("after inpaint",matInpaint);
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//the result is :if "the writing obscured a real object edge in a picture",the result is bad
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/************************************************************************/
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/* 7. Practice histogram equalization on images that you load in, and report the
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results. */
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/************************************************************************/
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Mat matSrc = imread(argv[1]);
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vector<Mat> planes;
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split(matSrc,planes);
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imshow("b",planes[0]);
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imshow("g",planes[1]);
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imshow("r",planes[2]);
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cv::equalizeHist(planes[0],planes[0]);
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cv::equalizeHist(planes[1],planes[1]);
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cv::equalizeHist(planes[2],planes[2]);
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imshow("bh",planes[0]);
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imshow("gh",planes[1]);
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imshow("rh",planes[2]);
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waitKey();
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return 0;
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}

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