我正在尝试从视频流中推断出一些已被修改为难以识别的QR码。我必须使用OpenCV。问题是该代码只能识别清晰可见的qr代码，而其必须识别的qr代码却模糊不清。我相信问题是一些参数，但我找不到它。根据您的说法，问题出在哪里？
我的代码：
#include <opencv2/opencv.hpp>
#include <iostream>
#include <cmath>
using namespace cv;
using namespace std;
const int CV_QR_NORTH = 0;
const int CV_QR_EAST = 1;
const int CV_QR_SOUTH = 2;
const int CV_QR_WEST = 3;
int counter = 0;
float cv_distance(Point2f P, Point2f Q); // Get Distance between two points
float cv_lineEquation(Point2f L, Point2f M, Point2f J); // Perpendicular Distance of a Point J from line formed by Points L and M; Solution to equation of the line Val = ax+by+c
float cv_lineSlope(Point2f L, Point2f M, int& alignement); // Slope of a line by two Points L and M on it; Slope of line, S = (x1 -x2) / (y1- y2)
void cv_getVertices(vector<vector<Point> > contours, int c_id, float slope, vector<Point2f>& X);
void cv_updateCorner(Point2f P, Point2f ref, float& baseline, Point2f& corner);
void cv_updateCornerOr(int orientation, vector<Point2f> IN, vector<Point2f> &OUT);
bool getIntersectionPoint(Point2f a1, Point2f a2, Point2f b1, Point2f b2, Point2f& intersection);
float cross(Point2f v1, Point2f v2);
// Start of Main Loop
//------------------------------------------------------------------------------------------------------------------------
int main(int argc, char **argv)
{
VideoCapture capture;
capture.open("video.mp4");
//Mat image = imread(argv[1]);
Mat image;
if (!capture.isOpened()) {
cerr << " ERR: Unable find input Video source." << endl;
return -1;
}
//Step : Capture a frame from Image Input for creating and initializing manipulation variables
//Info : Inbuilt functions from OpenCV
//Note :
capture >> image;
if (image.empty()) {
cerr << "ERR: Unable to query image from capture device.\n" << endl;
return -1;
}
// Creation of Intermediate 'Image' Objects required later
Mat gray(image.size(), CV_MAKETYPE(image.depth(), 1)); // To hold Grayscale Image
Mat edges(image.size(), CV_MAKETYPE(image.depth(), 1)); // To hold Grayscale Image
Mat traces(image.size(), CV_8UC3); // For Debug Visuals
Mat qr, qr_raw, qr_gray, qr_thres;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
vector<Point> pointsseq; //used to save the approximated sides of each contour
int mark, A, B, C, top, right, bottom, median1, median2, outlier;
float AB, BC, CA, dist, slope, areat, arear, areab, large, padding;
int align, orientation;
int DBG = 1; // Debug Flag
int key = 0;
while (key != 'q') // While loop to query for Image Input frame
{
traces = Scalar(0, 0, 0);
qr_raw = Mat::zeros(100, 100, CV_8UC3);
qr = Mat::zeros(100, 100, CV_8UC3);
qr_gray = Mat::zeros(100, 100, CV_8UC1);
qr_thres = Mat::zeros(100, 100, CV_8UC1);
capture >> image; // Capture Image from Image Input
cvtColor(image, gray, CV_RGB2GRAY); // Convert Image captured from Image Input to GrayScale
Canny(gray, edges, 100, 200, 3); // Apply Canny edge detection on the gray image
findContours(edges, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE);
mark = 0; // Reset all detected marker count for this frame
// Get Moments for all Contours and the mass centers
vector<Moments> mu(contours.size());
vector<Point2f> mc(contours.size());
for (int i = 0; i < contours.size(); i++)
{
mu[i] = moments(contours[i], false);
mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
}
// Start processing the contour data
// Find Three repeatedly enclosed contours A,B,C
// NOTE: 1. Contour enclosing other contours is assumed to be the three Alignment markings of the QR code.
// 2. Alternately, the Ratio of areas of the "concentric" squares can also be used for identifying base Alignment markers.
// The below demonstrates the first method
for (int i = 0; i < contours.size(); i++)
{
//Find the approximated polygon of the contour we are examining
approxPolyDP(contours[i], pointsseq, arcLength(contours[i], true)*0.02, true);
if (pointsseq.size() == 4) // only quadrilaterals contours are examined
{
int k = i;
int c = 0;
while (hierarchy[k][2] != -1)
{
k = hierarchy[k][2];
c = c + 1;
}
if (hierarchy[k][2] != -1)
c = c + 1;
if (c >= 5)
{
if (mark == 0) A = i;
else if (mark == 1) B = i; // i.e., A is already found, assign current contour to B
else if (mark == 2) C = i; // i.e., A and B are already found, assign current contour to C
mark = mark + 1;
}
}
}
if (mark >= 3) // Ensure we have (atleast 3; namely A,B,C) 'Alignment Markers' discovered
{
// We have found the 3 markers for the QR code; Now we need to determine which of them are 'top', 'right' and 'bottom' markers
// Determining the 'top' marker
// Vertex of the triangle NOT involved in the longest side is the 'outlier'
AB = cv_distance(mc[A], mc[B]);
BC = cv_distance(mc[B], mc[C]);
CA = cv_distance(mc[C], mc[A]);
if (AB > BC && AB > CA)
{
outlier = C; median1 = A; median2 = B;
}
else if (CA > AB && CA > BC)
{
outlier = B; median1 = A; median2 = C;
}
else if (BC > AB && BC > CA)
{
outlier = A; median1 = B; median2 = C;
}
top = outlier; // The obvious choice
dist = cv_lineEquation(mc[median1], mc[median2], mc[outlier]); // Get the Perpendicular distance of the outlier from the longest side
slope = cv_lineSlope(mc[median1], mc[median2], align); // Also calculate the slope of the longest side
// Now that we have the orientation of the line formed median1 & median2 and we also have the position of the outlier w.r.t. the line
// Determine the 'right' and 'bottom' markers
if (align == 0)
{
bottom = median1;
right = median2;
}
else if (slope < 0 && dist < 0) // Orientation - North
{
bottom = median1;
right = median2;
orientation = CV_QR_NORTH;
}
else if (slope > 0 && dist < 0) // Orientation - East
{
right = median1;
bottom = median2;
orientation = CV_QR_EAST;
}
else if (slope < 0 && dist > 0) // Orientation - South
{
right = median1;
bottom = median2;
orientation = CV_QR_SOUTH;
}
else if (slope > 0 && dist > 0) // Orientation - West
{
bottom = median1;
right = median2;
orientation = CV_QR_WEST;
}
// To ensure any unintended values do not sneak up when QR code is not present
float area_top, area_right, area_bottom;
if (top < contours.size() && right < contours.size() && bottom < contours.size() && contourArea(contours[top]) > 10 && contourArea(contours[right]) > 10 && contourArea(contours[bottom]) > 10)
{
vector<Point2f> L, M, O, tempL, tempM, tempO;
Point2f N;
vector<Point2f> src, dst; // src - Source Points basically the 4 end co-ordinates of the overlay image
// dst - Destination Points to transform overlay image
Mat warp_matrix;
cv_getVertices(contours, top, slope, tempL);
cv_getVertices(contours, right, slope, tempM);
cv_getVertices(contours, bottom, slope, tempO);
cv_updateCornerOr(orientation, tempL, L); // Re-arrange marker corners w.r.t orientation of the QR code
cv_updateCornerOr(orientation, tempM, M); // Re-arrange marker corners w.r.t orientation of the QR code
cv_updateCornerOr(orientation, tempO, O); // Re-arrange marker corners w.r.t orientation of the QR code
int iflag = getIntersectionPoint(M[1], M[2], O[3], O[2], N);
src.push_back(L[0]);
src.push_back(M[1]);
src.push_back(N);
src.push_back(O[3]);
dst.push_back(Point2f(0, 0));
dst.push_back(Point2f(qr.cols, 0));
dst.push_back(Point2f(qr.cols, qr.rows));
dst.push_back(Point2f(0, qr.rows));
if (src.size() == 4 && dst.size() == 4) // Failsafe for WarpMatrix Calculation to have only 4 Points with src and dst
{
warp_matrix = getPerspectiveTransform(src, dst);
warpPerspective(image, qr_raw, warp_matrix, Size(qr.cols, qr.rows));
copyMakeBorder(qr_raw, qr, 10, 10, 10, 10, BORDER_CONSTANT, Scalar(255, 255, 255));
cvtColor(qr, qr_gray, CV_RGB2GRAY);
threshold(qr_gray, qr_thres, 127, 255, CV_THRESH_BINARY);
//threshold(qr_gray, qr_thres, 0, 255, CV_THRESH_OTSU);
//for( int d=0 ; d < 4 ; d++){ src.pop_back(); dst.pop_back(); }
}
//Draw contours on the image
drawContours(image, contours, top, Scalar(255, 200, 0), 2, 8, hierarchy, 0);
drawContours(image, contours, right, Scalar(0, 0, 255), 2, 8, hierarchy, 0);
drawContours(image, contours, bottom, Scalar(255, 0, 100), 2, 8, hierarchy, 0);
// Insert Debug instructions here
if (DBG == 1)
{
// Debug Prints
// Visualizations for ease of understanding
if (slope > 5)
circle(traces, Point(10, 20), 5, Scalar(0, 0, 255), -1, 8, 0);
else if (slope < -5)
circle(traces, Point(10, 20), 5, Scalar(255, 255, 255), -1, 8, 0);
// Draw contours on Trace image for analysis
drawContours(traces, contours, top, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
drawContours(traces, contours, right, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
drawContours(traces, contours, bottom, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
// Draw points (4 corners) on Trace image for each Identification marker
circle(traces, L[0], 2, Scalar(255, 255, 0), -1, 8, 0);
circle(traces, L[1], 2, Scalar(0, 255, 0), -1, 8, 0);
circle(traces, L[2], 2, Scalar(0, 0, 255), -1, 8, 0);
circle(traces, L[3], 2, Scalar(128, 128, 128), -1, 8, 0);
circle(traces, M[0], 2, Scalar(255, 255, 0), -1, 8, 0);
circle(traces, M[1], 2, Scalar(0, 255, 0), -1, 8, 0);
circle(traces, M[2], 2, Scalar(0, 0, 255), -1, 8, 0);
circle(traces, M[3], 2, Scalar(128, 128, 128), -1, 8, 0);
circle(traces, O[0], 2, Scalar(255, 255, 0), -1, 8, 0);
circle(traces, O[1], 2, Scalar(0, 255, 0), -1, 8, 0);
circle(traces, O[2], 2, Scalar(0, 0, 255), -1, 8, 0);
circle(traces, O[3], 2, Scalar(128, 128, 128), -1, 8, 0);
// Draw point of the estimated 4th Corner of (entire) QR Code
circle(traces, N, 2, Scalar(255, 255, 255), -1, 8, 0);
// Draw the lines used for estimating the 4th Corner of QR Code
line(traces, M[1], N, Scalar(0, 0, 255), 1, 8, 0);
line(traces, O[3], N, Scalar(0, 0, 255), 1, 8, 0);
// Show the Orientation of the QR Code wrt to 2D Image Space
int fontFace = FONT_HERSHEY_PLAIN;
if (orientation == CV_QR_NORTH)
{
putText(traces, "NORTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
}
else if (orientation == CV_QR_EAST)
{
putText(traces, "EAST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
}
else if (orientation == CV_QR_SOUTH)
{
putText(traces, "SOUTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
}
else if (orientation == CV_QR_WEST)
{
putText(traces, "WEST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
}
// Debug Prints
imwrite("out.bmp", qr_thres);
}
}
}
imshow("Image", image);
imshow("Traces", traces);
imshow("QR code", qr_thres);
key = waitKey(2); // OPENCV: wait for 1ms before accessing next frame
} // End of 'while' loop
return 0;
}
// End of Main Loop
//--------------------------------------------------------------------------------------
// Routines used in Main loops
// Function: Routine to get Distance between two points
// Description: Given 2 points, the function returns the distance
float cv_distance(Point2f P, Point2f Q)
{
return sqrt(pow(abs(P.x - Q.x), 2) + pow(abs(P.y - Q.y), 2));
}
// Function: Perpendicular Distance of a Point J from line formed by Points L and M; Equation of the line ax+by+c=0
// Description: Given 3 points, the function derives the line quation of the first two points,
// calculates and returns the perpendicular distance of the the 3rd point from this line.
float cv_lineEquation(Point2f L, Point2f M, Point2f J)
{
float a, b, c, pdist;
a = -((M.y - L.y) / (M.x - L.x));
b = 1.0;
c = (((M.y - L.y) / (M.x - L.x)) * L.x) - L.y;
// Now that we have a, b, c from the equation ax + by + c, time to substitute (x,y) by values from the Point J
pdist = (a * J.x + (b * J.y) + c) / sqrt((a * a) + (b * b));
return pdist;
}
// Function: Slope of a line by two Points L and M on it; Slope of line, S = (x1 -x2) / (y1- y2)
// Description: Function returns the slope of the line formed by given 2 points, the alignement flag
// indicates the line is vertical and the slope is infinity.
float cv_lineSlope(Point2f L, Point2f M, int& alignement)
{
float dx, dy;
dx = M.x - L.x;
dy = M.y - L.y;
if (dy != 0)
{
alignement = 1;
return (dy / dx);
}
else // Make sure we are not dividing by zero; so use 'alignement' flag
{
alignement = 0;
return 0.0;
}
}
// Function: Routine to calculate 4 Corners of the Marker in Image Space using Region partitioning
// Theory: OpenCV Contours stores all points that describe it and these points lie the perimeter of the polygon.
// The below function chooses the farthest points of the polygon since they form the vertices of that polygon,
// exactly the points we are looking for. To choose the farthest point, the polygon is divided/partitioned into
// 4 regions equal regions using bounding box. Distance algorithm is applied between the centre of bounding box
// every contour point in that region, the farthest point is deemed as the vertex of that region. Calculating
// for all 4 regions we obtain the 4 corners of the polygon ( - quadrilateral).
void cv_getVertices(vector<vector<Point> > contours, int c_id, float slope, vector<Point2f>& quad)
{
Rect box;
box = boundingRect(contours[c_id]);
Point2f M0, M1, M2, M3;
Point2f A, B, C, D, W, X, Y, Z;
A = box.tl();
B.x = box.br().x;
B.y = box.tl().y;
C = box.br();
D.x = box.tl().x;
D.y = box.br().y;
W.x = (A.x + B.x) / 2;
W.y = A.y;
X.x = B.x;
X.y = (B.y + C.y) / 2;
Y.x = (C.x + D.x) / 2;
Y.y = C.y;
Z.x = D.x;
Z.y = (D.y + A.y) / 2;
float dmax[4];
dmax[0] = 0.0;
dmax[1] = 0.0;
dmax[2] = 0.0;
dmax[3] = 0.0;
float pd1 = 0.0;
float pd2 = 0.0;
if (slope > 5 || slope < -5)
{
for (int i = 0; i < contours[c_id].size(); i++)
{
pd1 = cv_lineEquation(C, A, contours[c_id][i]); // Position of point w.r.t the diagonal AC
pd2 = cv_lineEquation(B, D, contours[c_id][i]); // Position of point w.r.t the diagonal BD
if ((pd1 >= 0.0) && (pd2 > 0.0))
{
cv_updateCorner(contours[c_id][i], W, dmax[1], M1);
}
else if ((pd1 > 0.0) && (pd2 <= 0.0))
{
cv_updateCorner(contours[c_id][i], X, dmax[2], M2);
}
else if ((pd1 <= 0.0) && (pd2 < 0.0))
{
cv_updateCorner(contours[c_id][i], Y, dmax[3], M3);
}
else if ((pd1 < 0.0) && (pd2 >= 0.0))
{
cv_updateCorner(contours[c_id][i], Z, dmax[0], M0);
}
else
continue;
}
}
else
{
int halfx = (A.x + B.x) / 2;
int halfy = (A.y + D.y) / 2;
for (int i = 0; i < contours[c_id].size(); i++)
{
if ((contours[c_id][i].x < halfx) && (contours[c_id][i].y <= halfy))
{
cv_updateCorner(contours[c_id][i], C, dmax[2], M0);
}
else if ((contours[c_id][i].x >= halfx) && (contours[c_id][i].y < halfy))
{
cv_updateCorner(contours[c_id][i], D, dmax[3], M1);
}
else if ((contours[c_id][i].x > halfx) && (contours[c_id][i].y >= halfy))
{
cv_updateCorner(contours[c_id][i], A, dmax[0], M2);
}
else if ((contours[c_id][i].x <= halfx) && (contours[c_id][i].y > halfy))
{
cv_updateCorner(contours[c_id][i], B, dmax[1], M3);
}
}
}
quad.push_back(M0);
quad.push_back(M1);
quad.push_back(M2);
quad.push_back(M3);
}
// Function: Compare a point if it more far than previously recorded farthest distance
// Description: Farthest Point detection using reference point and baseline distance
void cv_updateCorner(Point2f P, Point2f ref, float& baseline, Point2f& corner)
{
float temp_dist;
temp_dist = cv_distance(P, ref);
if (temp_dist > baseline)
{
baseline = temp_dist; // The farthest distance is the new baseline
corner = P; // P is now the farthest point
}
}
// Function: Sequence the Corners wrt to the orientation of the QR Code
void cv_updateCornerOr(int orientation, vector<Point2f> IN, vector<Point2f> &OUT)
{
Point2f M0, M1, M2, M3;
if (orientation == CV_QR_NORTH)
{
M0 = IN[0];
M1 = IN[1];
M2 = IN[2];
M3 = IN[3];
}
else if (orientation == CV_QR_EAST)
{
M0 = IN[1];
M1 = IN[2];
M2 = IN[3];
M3 = IN[0];
}
else if (orientation == CV_QR_SOUTH)
{
M0 = IN[2];
M1 = IN[3];
M2 = IN[0];
M3 = IN[1];
}
else if (orientation == CV_QR_WEST)
{
M0 = IN[3];
M1 = IN[0];
M2 = IN[1];
M3 = IN[2];
}
OUT.push_back(M0);
OUT.push_back(M1);
OUT.push_back(M2);
OUT.push_back(M3);
}
// Function: Get the Intersection Point of the lines formed by sets of two points
bool getIntersectionPoint(Point2f a1, Point2f a2, Point2f b1, Point2f b2, Point2f& intersection)
{
Point2f p = a1;
Point2f q = b1;
Point2f r(a2 - a1);
Point2f s(b2 - b1);
if (cross(r, s) == 0) { return false; }
float t = cross(q - p, s) / cross(r, s);
intersection = p + t * r;
return true;
}
float cross(Point2f v1, Point2f v2)
{
return v1.x*v2.y - v1.y*v2.x;
}
程序应从视频中识别出以下QR码：
https://drive.google.com/file/d/1uqZSJCpBML8vb7AuDU9KpTeXHt-3IAPi/view?usp=sharing
https://drive.google.com/open?id=1VDj2DalqB-0lWaFwVC_Nz6nT-8rUZ1NA
https://drive.google.com/open?id=12L8V2WuHJ-xomOgQqn1CIUh2s8BD24OZ
https://drive.google.com/open?id=1CRCBrczOMzdSLuwb-mYoU5d_iB2MIVxJ