Ejemplos de síntesis detalladas OpenCV transformación de perspectiva (versión c) - detección de tarjeta de seguridad social y corrección

 

Ejemplos en el presente documento comparten un amplio ejemplos de código específico transformación de perspectiva OpenCV para la referencia, de la siguiente

Caso Antecedentes: la imagen se distorsiona después de la corrección

 

ideas del programa: segmentación binaria gris, la operación de cierre, para encontrar el perfil, la detección línea de Hough, clasificación recta, ecuaciones lineales, la intersección de la línea recta, la matriz de punto de vista, la transformación de perspectiva.

 

#include<opencv2\opencv.hpp>
using namespace cv;
using namespace std;
int main(int arc, char** argv) { 
 Mat src = imread("1.jpg");
 namedWindow("input", CV_WINDOW_AUTOSIZE);
 imshow("input", src);
 //灰度化
 Mat grayImg;
 cvtColor(src, grayImg, CV_BGR2GRAY);
 
 //二值化
 Mat binaryImg;
 threshold(grayImg, binaryImg, 0, 255, THRESH_BINARY_INV | THRESH_OTSU);
 
 //闭操作
 Mat kernel = getStructuringElement(MORPH_RECT,Size(3,3));
 morphologyEx(binaryImg, binaryImg, MORPH_CLOSE,kernel,Point(-1,-1) ,3);
 imshow("output", binaryImg);
 
 //寻找轮廓
 Mat draw = Mat::zeros(src.size(), CV_8UC3);
 vector<vector<Point>>contours;
 findContours(binaryImg, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point());
 for (int i = 0; i < contours.size(); i++) {
 Rect rect = boundingRect(contours[i]);
 if (rect.width < src.cols / 2 && rect.height < src.rows / 2)continue;
 drawContours(draw, contours, i, Scalar(0, 0, 255), 2);
 }
 imshow("output2", draw);
 
 //霍夫直线检测
 vector<Vec4i> lines;
 cvtColor(draw, draw, CV_BGR2GRAY);
 HoughLinesP(draw, lines, 1, CV_PI / 180, src.rows/2,src.rows/2,0);
 Mat draw2 = Mat::zeros(src.size(), CV_8UC3);
 for (int j = 0; j < lines.size(); j++) {
 Vec4i ln = lines[j];
 line(draw2, Point(ln[0], ln[1]), Point(ln[2], ln[3]), Scalar(0, 255, 0), 2); 
 }
 printf("number of line:%d\n", lines.size());
 imshow("output3", draw2);
 
 //寻找与定位直线
 Vec4i topLine,bottomLine,leftLine,rightLine;
 for (int j = 0; j < lines.size(); j++) {
 Vec4i ln = lines[j];
 if (ln[1] < src.rows / 2 && ln[3] < src.rows / 2) {
  topLine = ln;
 }
 if (ln[1] > src.rows / 2 && ln[3] > src.rows / 2) {
  bottomLine = ln;
 }
 if (ln[0] < src.cols / 2 && ln[2] < src.cols / 2) {
  leftLine = ln;
 }
 if (ln[0] > src.cols / 2 && ln[2] > src.cols / 2) {
  rightLine = ln;
 }
 }
 cout << "topLine:p1(x,y)=" << topLine[0] << "," << topLine[1]<<" " << "p2(x,y)=" << topLine[2] << "," << topLine[3] << endl;
 cout << "bottomLine:p1(x,y)=" << bottomLine[0] << "," << bottomLine[1] << " " << "p2(x,y)=" << bottomLine[2] << "," << bottomLine[3] << endl;
 cout << "leftLine:p1(x,y)=" << leftLine[0] << "," << leftLine[1] << " " << "p2(x,y)=" << leftLine[2] << "," << leftLine[3] << endl;
 cout << "rightLine:p1(x,y)=" << rightLine[0] << "," << rightLine[1] << " " << "p2(x,y)=" << rightLine[2] << "," << rightLine[3] << endl;
 
 //求解直线方程
 float k1, c1;
 k1 = float((topLine[3] - topLine[1])) / float(topLine[2] - topLine[0]);
 c1 = topLine[1] - k1*topLine[0];
 float k2, c2;
 k2 = float((bottomLine[3] - bottomLine[1])) / float(bottomLine[2] - bottomLine[0]);
 c2 = bottomLine[1] - k2*bottomLine[0];
 float k3, c3;
 k3 = float((leftLine[3] - leftLine[1])) / float(leftLine[2] - leftLine[0]);
 c3 = leftLine[1] - k3*leftLine[0];
 float k4, c4;
 k4 = float((rightLine[3] - rightLine[1])) / float(rightLine[2] - rightLine[0]);
 c4 = rightLine[1] - k4*rightLine[0];
 
 //求解直线交点
 Point p1;
 p1.x = (int)((c1 - c3) / (k3 - k1));
 p1.y = (int)(k1*p1.x + c1);
 Point p2;
 p2.x = (int)((c1 - c4) / (k4 - k1));
 p2.y = (int)(k1*p2.x + c1);
 Point p3;
 p3.x = (int)((c2 - c4) / (k4 - k2));
 p3.y = (int)(k2*p3.x + c2);
 Point p4;
 p4.x = (int)((c2 - c3) / (k3 - k2));
 p4.y = (int)(k2*p4.x + c2);
 cout << "左上角:" << p1.x << "," << p1.y << endl;
 cout << "右上角:" << p2.x << "," << p2.y << endl;
 cout << "右下角:" << p3.x << "," << p3.y << endl;
 cout << "左下角:" << p4.x << "," << p4.y << endl;
 
 //画出交点
 circle(draw2, p1, 2, Scalar(0, 0, 255));
 circle(draw2, p2, 2, Scalar(0, 0, 255));
 circle(draw2, p3, 2, Scalar(0, 0, 255));
 circle(draw2, p4, 2, Scalar(0, 0, 255));
 imshow("output4", draw2);
 
 //透视变换
 vector<Point2f> srcCorners(4);
 srcCorners[0] = p1;
 srcCorners[1] = p2;
 srcCorners[2] = p3;
 srcCorners[3] = p4;
 vector<Point2f> dstCorners(4);
 dstCorners[0] = Point(0, 0);
 dstCorners[1] = Point(src.cols, 0);
 dstCorners[2] = Point(src.cols, src.rows);
 dstCorners[3] = Point(0, src.rows); 
 Mat warpMartrix = getPerspectiveTransform(srcCorners, dstCorners);//Mat warpMartrix = findHomography(srcCorners, dstCorners); 
 Mat result = Mat::zeros(src.size(), -1);
 warpPerspective(src, result, warpMartrix, result.size(),INTER_LINEAR);
 imshow("output5", result);
 waitKey(0);
 return 0; 
}

 

La imagen original

Y la operación de cierre de la binarización

 

perfil que mira

 

recta Hough

Y la intersección de la línea recta

representaciones

Eso es todo por este artículo, quiero ayuda para aprender.

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