void houghTransform(cv::Mat img, float* &alpha)
{
// rotate for hough detection
img = rotateImg(img, 90);
// canny edge detection
cv::Mat imgMap;
cannyDetector(img, imgMap); // retrives a binary image with contours of orange spots
cvtColor(imgMap, mapDraw, CV_GRAY2BGR); //image for drawing
// detect line ROI1
cv::Rect roi1 = cv::Rect(0, 160, 120, 320);
cv::rectangle(mapDraw, cv::Point(roi1.x,roi1.y), cv::Point(roi1.x+roi1.width,roi1.y+roi1.height), cv::Scalar( 0, 55, 255 ), +1, 4 );
std::vector<cv::Vec4i> lines;
HoughLinesP(imgMap(roi1), lines, 1, CV_PI/180, 50, 50, 20 );
int p1x, p1y, p2x, p2y; // line start and final point
if (lines.size() > 0)
{
lineParam(roi1, lines, p1x, p1y, p2x, p2y);
*alpha = atan((float)(p2y-p1y)/(p2x-p1x));
cv::line(mapDraw, cv::Point (p1x,p1y), cv::Point(p2x,p2y), cv::Scalar(0, 255, 0), 2, 8); //draw line
}
else *alpha = 999;
*alpha = atan((float)(p2y-p1y)/(p2x-p1x));
//result visualization
mapDraw = rotateImg(mapDraw, -90);
cv::imshow("hough", mapDraw);
}
a
void lineDetector(cv::Mat imgSrc, float &alpha, float &lineEnd)
{
// rotate image needed for hough detection
imgSrc = rotateImg(imgSrc, 90);
// detection of orange contours
cv::Mat imgMapColor, imgMapMorpho, imgDraw;
imgDraw = cv::Mat::zeros( imgSrc.size(), imgSrc.type() );
int h_min, h_max, m_e, m_d;
h_min = 0; h_max = 10; // orange min and max hue
m_e = 5; m_d = 15; // erode and dilate morphological kernels
ml::findColoredContour(imgSrc, imgMapColor, imgMapMorpho, h_min, h_max, m_e, m_d);
// parameters of line
int roi_k; // roi counter (from 0 to 3)
std::vector<std::vector<int> > linePoints; // point coordinates of the segemented line
std::vector<float> lineAngles; // anlges of the segemented line
// find line in ROI
roi_k = 0; std::cout<<std::endl<<"Start line detector"<<std::endl;
while(roi_k < 4)
{
lineROI(roi_k, imgMapMorpho, imgDraw, linePoints, lineAngles);
roi_k++;
}
if(linePoints.size() > 0) // print line found
{
std::cout<<"Printing lines angles ending points... "<<std::endl;
for(int i = 0; i < linePoints.size(); i++){
std::cout<<"Line "<<i<<": "<<linePoints[i][2]<<" "<<linePoints[i][3]<<" "<<std::endl;
std::cout<<"Angle "<<i<<": "<<lineAngles[i]<<std::endl;
}
alpha = lineAngles[0];
lineEnd = linePoints[linePoints.size() - 1][2];
}
else
{
std::cout<<"No line found"<<std::endl;
alpha = 999;
lineEnd = 999;
}
//result visualization
imgDraw = rotateImg(imgDraw, -90);
//cv::imshow("source", imgSrc);
cv::imshow("hough", imgDraw); cv::waitKey(10);
}
cv::Mat getSyntheticImage(const Mat& image) {
int rand_type = rand();
Mat result = image.clone();
if (rand_type % 2 == 0) {
int ran_x = rand() % 5 - 2;
int ran_y = rand() % 5 - 2;
result = translateImg(result, ran_x, ran_y);
}
else if (rand_type % 2 != 0) {
float angle = float(rand() % 15 - 7);
result = rotateImg(result, angle);
}
return result;
}
int _tmain(int argc, _TCHAR* argv[])
{
srand((int)time(0));
////大凹点配置
//int minR = 25;
//int maxR = 60;
////小凹点 水渍配置
//int minR = 15;
//int maxR = 30;
////划痕配置
//int minR = 30;
//int maxR = 160;
//指纹配置
int minR = 60;
int maxR = 200;
int deflection = 50;//中心点随机偏离距离
//cv::Mat src = cv::imread("A9划痕凹点_x3.jpg");
//cv::Point center = cv::Point(962, 4394);//大凹点
//string path = "samples\\大凹点A_";
//cv::Point center = cv::Point(1398, 4473);//小凹点
//string path = "samples\\小凹点A_";
//cv::Point center = cv::Point(882, 6244);
//string path = "samples\\水渍A4_";
//cv::Point center = cv::Point(1677, 3400);
//string path = "samples\\划痕A2_";
//cv::Point center = cv::Point(2110, 9000);//小凹点
//string path = "samples\\釉面A2_";
//cv::Mat src = cv::imread("D9划痕凹点_x3.jpg");
//cv::Point center = cv::Point(852, 5638);//大凹点
//string path = "samples\\大凹点D_";
//cv::Point center = cv::Point(1284, 5708);//小凹点
//string path = "samples\\小凹点D_";
//cv::Point center = cv::Point(1832, 9057);//小凹点
//string path = "samples\\划痕D2_";
//cv::Point center = cv::Point(992, 10057);//小凹点
//string path = "samples\\釉面D2_";
//cv::Mat src = cv::imread("A14杂质_x3.jpg");
//cv::Point center = cv::Point(1300, 2050);
//string path = "samples\\指纹A2_";
//cv::Point center = cv::Point(2130, 7226);
//string path = "samples\\杂质A_";
//cv::Mat src = cv::imread("D14杂质_x3.jpg");
//cv::Point center = cv::Point(1200, 9400);
//string path = "samples\\指纹D2_";
//cv::Point center = cv::Point(2029, 7711);
//string path = "samples\\杂质D_";
//cv::Mat src = cv::imread("A31崩角_x3.jpg");
//cv::Point center = cv::Point(2600,7900);
//string path = "samples\\水纹A4_";
cv::Mat src = cv::imread("D31崩角_x3.jpg");
cv::Point center = cv::Point(1800, 3100);
string path = "samples\\水纹D4_";
int r = 400;
cv::Mat ROI = src(cv::Rect(center.x - r, center.y - r, r + r, r + r));
for (size_t i = 1; i <= 10; i++)
{
double angle = random(361);
cv::Mat rotateMat = cv::getRotationMatrix2D(cv::Point(r, r), angle, 1);
cv::Mat rotateImg;
cv::warpAffine(ROI, rotateImg, rotateMat, ROI.size());
int offsetX = random(deflection) - deflection/2;
int offsetY = random(deflection) - deflection/2;
int range = abs(random(maxR - minR)) + minR;
cv::Mat ROI2 = rotateImg(cv::Rect(r - offsetX - range, r - offsetY - range, range + range, range + range));
char num[4];
sprintf(num, "%03d", i);
stringstream ss;
ss << path << num << ".jpg";
cv::imwrite(ss.str(), ROI2);
//cv::imshow("1", ROI2);
//cv::waitKey(0);
}
return 0;
}
int main(int argc, char** argv)
{
int height ,width ,step ,channels;
int same, lighter;
float thresh;
uchar *dataB, *dataG, *dataR, *dataGray, *dataD;
uchar b1, g1, r1, b2, g2, r2;
int w = 3;
int th = 50;
int idx1, idx2;
cv::Mat img = cv::imread(argv[1]);
height = img.rows;
width = img.cols;
cv::namedWindow("Image0", cv::WINDOW_NORMAL);
cv::Mat textImg(1000, 1200, CV_8UC1, cv::Scalar(255));
cv::putText(textImg, "Original Image:", cv::Point(400, 500), cv::FONT_HERSHEY_SIMPLEX, 2, cv::Scalar(0, 0, 0));
//cv::imshow("Image0", textImg);
//cv::waitKey();
//cv::imshow("Image0", img);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Next: Apply SUSAN algorithm to detect edge and cross.", cv::Point(200, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
std::vector<cv::Mat> imgChannels;
cv::split(img, imgChannels);
cv::Mat dstSusan(height, width, CV_8UC1, cv::Scalar(0));
cv::Mat grayImg(height, width, CV_8UC1, cv::Scalar(0));
step = imgChannels[0].step[0];
dataB = imgChannels[0].data;
dataG = imgChannels[1].data;
dataR = imgChannels[2].data;
dataGray = grayImg.data;
dataD= dstSusan.data;
for (int x = w; x < width-w; x++)
{
for (int y = w; y < height-w; y++)
{
same = 0;
idx1 = x + y * step;
b1 = dataB[idx1];
g1 = dataG[idx1];
r1 = dataR[idx1];
for (int u = 0; u < w+1; u++)
{
for (int v = 0; v < w+1; v++)
{
if (u + v == 0)
{
continue;
}
idx2 = (x+u) + (y+v) * step;
b2 = dataB[idx2];
g2 = dataG[idx2];
r2 = dataR[idx2];
if (calc_dist(b1, g1, r1, b1, g2, r2) < th)
{
same += 1;
}
idx2 = (x-u) + (y+v) * step;
b2 = dataB[idx2];
g2 = dataG[idx2];
r2 = dataR[idx2];
if (u != 0 && calc_dist(b1, g1, r1, b1, g2, r2) < th)
{
same += 1;
}
idx2 = (x+u) + (y-v) * step;
b2 = dataB[idx2];
g2 = dataG[idx2];
r2 = dataR[idx2];
if (v != 0 && calc_dist(b1, g1, r1, b1, g2, r2) < th)
{
same += 1;
}
idx2 = (x-u) + (y-v) * step;
b2 = dataB[idx2];
g2 = dataG[idx2];
r2 = dataR[idx2];
if (u != 0 && v != 0 && calc_dist(b1, g1, r1, b1, g2, r2) < th)
{
same += 1;
}
}
}
dataD[idx1] = uchar(255.0 * float(same) / ((2*w+1) * (2*w+1) - 1));
if (dataD[idx1] < 128)
{
dataD[idx1] = 255;
}
else
{
dataD[idx1] = 0;
}
}
}
//cv::imshow("Image0", dstSusan);
cv::imwrite("outimg_1.jpg", dstSusan);
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Next: Apply Hough algorithm to detect lines.", cv::Point(300, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::waitKey();
//cv::imshow("Image0", textImg);
//cv::waitKey();
//Hough line detection
std::vector<cv::Vec4i> lines;
HoughLinesP(dstSusan, lines, 1, CV_PI/180, 80, 500, 20);
double thetaSum = 0.0;
int thetaNum = 0;
double theta;
for(size_t i = 0; i < lines.size(); i++)
{
cv::Vec4i l = lines[i];
cv::line(img, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(186,88,255), 1, CV_AA);
if (l[0] == l[2])
{
theta = CV_PI / 2;
}
else
{
theta = std::atan(-double(l[3]-l[1]) / (l[2] - l[0]));
}
if (theta >= -CV_PI / 4 && theta <= CV_PI / 4)
{
thetaSum += theta;
thetaNum += 1;
}
}
theta = -thetaSum / thetaNum * 180 / CV_PI;
//cv::imshow("Image0", img);
cv::imwrite("outimg_2.jpg", img);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
std::ostringstream textStr;
textStr << "Find " << lines.size() << " lines.";
cv::putText(textImg, textStr.str(), cv::Point(500, 400), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
textStr.str(std::string());
textStr.clear();
textStr << "Rotating angle is " << theta << " degree.";
cv::putText(textImg, textStr.str(), cv::Point(350, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Next: Rotating the image.", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 700), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
img.release();
img = cv::imread(argv[1]);
imgChannels[0].release();
imgChannels[1].release();
imgChannels[2].release();
imgChannels.clear();
cv::Mat rotateImg(height, width, CV_8UC3);
cv::Point2f center;
center.x = float(width / 2.0 + 0.5);
center.y = float(height / 2.0 + 0.5);
cv::Mat affineMat = getRotationMatrix2D(center, theta, 1);
cv::warpAffine(img,rotateImg, affineMat, cv::Size(width, height), CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS);
//cv::imshow("Image0", rotateImg);
cv::imwrite("outimg_3.jpg", rotateImg);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Next: Transform the image to gray scale.", cv::Point(300, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
cv::split(rotateImg, imgChannels);
dataB = imgChannels[0].data;
dataG = imgChannels[1].data;
dataR = imgChannels[2].data;
step = imgChannels[0].step[0];
//imgChannels[2].setTo(cv::Scalar(0));
for (int x = 0; x < rotateImg.cols; x++)
{
for (int y = 0; y < rotateImg.rows; y++)
{
int idx = x + y * step;
if (dataB[idx] < dataG[idx] && dataB[idx] < dataR[idx])
{
dataG[idx] = dataB[idx];
dataR[idx] = dataB[idx];
}
if (dataG[idx] < dataB[idx] && dataG[idx] < dataR[idx])
{
dataB[idx] = dataG[idx];
dataR[idx] = dataG[idx];
}
if (dataR[idx] < dataB[idx] && dataR[idx] < dataG[idx])
{
dataB[idx] = dataR[idx];
dataG[idx] = dataR[idx];
}
}
}
cv::Mat filterRedImg(rotateImg.rows, rotateImg.cols, CV_8UC3, cv::Scalar::all(255));
cv::merge(imgChannels, filterRedImg);
cv::cvtColor(filterRedImg, grayImg, CV_BGR2GRAY);
//cv::imshow("Image0", grayImg);
cv::imwrite("outimg_4.jpg", grayImg);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Next: Clean the noise.", cv::Point(450, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
step = grayImg.step[0];
for (int x = 0; x < width; x++)
{
for (int y = 0; y < height; y++)
{
int idx = x + y * step;
if (grayImg.data[idx] > 100)
//if(!is_gray(dataB[idx], dataG[idx], dataR[idx]))
{
grayImg.data[idx] = 255;
}
}
}
//cv::imshow("Image0", grayImg);
cv::imwrite("outimg_5.jpg", grayImg);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Next: Digitizing the curves.", cv::Point(400, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
cv::putText(textImg, "Press any key to continue...", cv::Point(400, 600), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
cv::Mat newImg(height, width, CV_8UC3, cv::Scalar::all(255));
SegmentFactory segFactory = SegmentFactory(0);
std::vector<Segment *> segments;
segFactory.makeSegments(grayImg, segments);
std::vector<Segment *>::iterator itr;
for (itr = segments.begin(); itr != segments.end(); itr++)
{
Segment *seg = *itr;
std::vector<SegmentLine *>::iterator itr_l;
for (itr_l = seg->m_lines.begin(); itr_l != seg->m_lines.end(); itr_l++)
{
SegmentLine *line = *itr_l;
cv::line(newImg, cv::Point(line->m_x1, line->m_y1), cv::Point(line->m_x2, line->m_y2), cv::Scalar(186,88,255), 1, CV_AA);
std::cout << line->m_x1 << ", " << line->m_y1 << ", " << line->m_x2 << ", " << line->m_y2 << std::endl;
}
}
//cv::imshow("Image0", newImg);
cv::imwrite("outimg_6.jpg", newImg);
//cv::waitKey();
textImg.setTo(cv::Scalar(255, 255, 255));
cv::putText(textImg, "Done.", cv::Point(550, 500), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255));
//cv::imshow("Image0", textImg);
//cv::waitKey();
return 0;
}
