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verbesserte Linienerkennung

pull/1/head
Baran Yasar 1 year ago
parent
commit
4e4d8d30eb
6 changed files with 66 additions and 64 deletions
  1. 10
    56
      Processing/processing.cpp
  2. 1
    1
      Processing/processing.h
  3. 43
    2
      Utils/utils.cpp
  4. 3
    2
      Utils/utils.h
  5. 1
    1
      autonomous_mode_main.cpp
  6. 8
    2
      lfr.cpp

+ 10
- 56
Processing/processing.cpp View File

@@ -23,66 +23,20 @@ void Processing::processImage(Mat& inputPicture, int thresholdValue, int gaussKe
// One (this) to do all kinds of stuff to the picture (grayscale conversion, threshold, gauss etc etc)
// And one (the other one) to segment the lines.
// No return value here as the input is passed by reference -> directly modified.
vector<Vec4i> lines;

cvtColor(inputPicture, inputPicture, COLOR_BGR2GRAY);
threshold(inputPicture, inputPicture, thresholdValue, 255, THRESH_BINARY);
GaussianBlur(inputPicture, inputPicture, Size(gaussKernelSize, gaussKernelSize), 0);
Canny(inputPicture, inputPicture, 50, 200, 3);

HoughLinesP(inputPicture, lines, 1, CV_PI/180, 150, 0, 0);
//Draw lines
for( size_t i = 0; i < lines.size(); i++ )
{
line( inputPicture, Point(lines[i][0], lines[i][1]),
Point( lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 );
}
vector<VectorOfLines> vectors;

Point point11;
Point point12;
Point point21;
Point point22;

for( size_t i = 0; i < lines.size(); i++ )
{
point11 = Point(lines[i][0], lines[i][1]);
point12 = Point( lines[i][2], lines[i][3]);
float gradient1 = VectorOfLines::calcGradient(point11, point12);
for( size_t j = 0; j < lines.size(); j++ )
{
if(j != i){
point21 = Point(lines[j][0], lines[j][1]);
point22 = Point(lines[j][2], lines[j][3]);
float gradient2 = VectorOfLines::calcGradient(point21, point22);
float gradient12 = VectorOfLines::calcGradient(point12, point21);
if((norm(gradient1 - gradient2) < 0.05) & (norm(gradient1 - gradient12) < 0.05))
{
//To Do: add line between 2 lines
}

}
}
}


imshow("Result", inputPicture);
waitKey(0);
destroyWindow("Result");

for( size_t i = 0; i < lines.size(); i++ )
{
line( inputPicture, Point(lines[i][0], lines[i][1]),
Point( lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 );
}
GaussianBlur(inputPicture, inputPicture, Size(gaussKernelSize, gaussKernelSize), 0);
Canny(inputPicture, inputPicture, 50, 100, 3);
}

std::vector<LFRLine> Processing::calculateLineSegments(const Mat& inputPicture)
std::vector<Vec4i> Processing::calculateLineSegments(const Mat& inputPicture)
{
//See following link
//https://stackoverflow.com/questions/45322630/how-to-detect-lines-in-opencv
return std::vector<LFRLine>();
vector<Vec4i> lines;
VectorOfLines linesInVectors;
HoughLinesP(inputPicture, lines, 1, CV_PI/360, 150, 0, 250);
//lines = linesInVectors.findMiddleLine(lines);
return lines;
}

+ 1
- 1
Processing/processing.h View File

@@ -21,5 +21,5 @@ public:

void processImage(Mat& inputPicture, int thresholdValue, int gaussKernelSize);

std::vector<LFRLine> calculateLineSegments(const Mat& inputPicture);
std::vector<Vec4i> calculateLineSegments(const Mat& inputPicture);
};

+ 43
- 2
Utils/utils.cpp View File

@@ -50,12 +50,53 @@ VectorOfLines::VectorOfLines()
{
}

float VectorOfLines::calcGradient(Point p0, Point p1)
VectorOfLines::~VectorOfLines()
{
return (p1.y - p0.y)/(p1.x - p0.x);
}

double VectorOfLines::calcGradient(Point p0, Point p1)
{
double gradient = (p1.y - p0.y)/(p1.x - p0.x + 1e-10);
return p1.x > p0.x ? gradient : - gradient;
}
float VectorOfLines::calcZeroPoint(cv::Point x, float m)
{
return 0.0;
}

double VectorOfLines::calcDistance(Point p0, Point p1)
{
return sqrt(pow(p1.y - p0.y, 2) + pow(p1.x - p0.x, 2));
}

vector<Vec4i> VectorOfLines::findMiddleLine(vector<Vec4i> &lines){
Point point11;
Point point12;
Point point21;
Point point22;
vector<Vec4i> middleLines;
for( size_t i = 0; i < (lines.size() - 1); i++ )
{
point11 = Point(lines[i][0], lines[i][1]);
point12 = Point( lines[i][2], lines[i][3]);
double gradient1 = VectorOfLines::calcGradient(point11, point12);

//Compare every Line with the other
for( size_t j = 0; j < (lines.size()); j++ )
{
if(j != i)
{
point21 = Point(lines[j][0], lines[j][1]);
point22 = Point(lines[j][2], lines[j][3]);
double gradient2 = VectorOfLines::calcGradient(point21, point22);
if(norm(gradient1 - gradient2) < 0.15)
{
middleLines.push_back(Vec4i((point11.x+point21.x)/2, (point11.y+point21.y)/2, (point12.x+point22.x)/2, (point12.y+point22.y)/2));
}
}
}
}
return middleLines;
}

+ 3
- 2
Utils/utils.h View File

@@ -55,8 +55,9 @@ class VectorOfLines{
float zeroPoint;
VectorOfLines();
~VectorOfLines();
static float calcGradient(Point x, Point y);
static double calcGradient(Point x, Point y);
float calcZeroPoint(cv::Point x, float m);

static double calcDistance(Point p0, Point p1);
vector<Vec4i> findMiddleLine(vector<Vec4i> &lines);

};

+ 1
- 1
autonomous_mode_main.cpp View File

@@ -9,7 +9,7 @@ int main(void)
const int thresholdBinary = 140;
const int videoHeight = 240;
const int videoWidth = 320;
const int gaussKernelSize = 11;
const int gaussKernelSize = 21;

LFR lfr(videoHeight, videoWidth, thresholdBinary, gaussKernelSize);
lfr.startLoop();

+ 8
- 2
lfr.cpp View File

@@ -23,8 +23,14 @@ void LFR::loop()
while(iAmLooping)
{
Mat image = input.readFile("C:\\Line-Following-Robot\\Test_data");
processing.processImage(image, this->thresholdBinary, this->gaussKernelSize);
std::vector<LFRLine> lines = processing.calculateLineSegments(image);
Mat processedImage = image;
processing.processImage(processedImage, this->thresholdBinary, this->gaussKernelSize);
std::vector<Vec4i> lines = processing.calculateLineSegments(processedImage);
for( size_t i = 0; i < lines.size(); i++ )
{
line( image, Point(lines[i][0], lines[i][1]),
Point( lines[i][2], lines[i][3]), (0,0,255), 1, 8 );
}
imshow("Display window", image);
char c = (char)waitKey(1);
}

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