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| #include <iostream> #include <raspicam/raspicam_cv.h> #include <opencv2/imgproc.hpp> #include <opencv2/highgui/highgui.hpp> using namespace std; using namespace cv; typedef struct { unsigned char r; unsigned char g; unsigned char b; } Color; typedef struct PosList { int x; int y; struct PosList *next; } PosList; int colordiff(Color a, Color b) { int dr, dg, db; dr = (int)((a.r < b.r) ? (b.r - a.r) : (a.r - b.r)); dg = (int)((a.g < b.g) ? (b.g - a.g) : (a.g - b.g)); db = (int)((a.b < b.b) ? (b.b - a.b) : (a.b - b.b)); return dr + dg + db; }PosList* newnode(int x, int y) { PosList *pos; pos = (PosList *)malloc(sizeof(PosList)); pos->x = x; pos->y = y; pos->next = NULL; return pos; }void delnode(PosList **pos) { free(*pos); *pos = NULL; }void pl_push(PosList **list, PosList *pos) { pos->next = *list; *list = pos; }PosList* pl_pop(PosList **list) { PosList *pos; pos = *list; *list = (*list)->next; return pos; }void dellist(PosList **list) { PosList *a, *b; a = *list; while (a != NULL) { b = a->next; delnode(&a); a = b; } }int contains(PosList *list, int x, int y) { while (list != NULL) { if (list->x == x && list->y == y) return 1; list = list->next; } return 0; }void rgrow(IplImage *source, IplImage *dest, Color color, int threshold) { PosList *list_n; PosList *node_r; PosList *list_r; Color curcolor; int x, y; int sx, sy; int dx, dy; int offset; int mindiff, curdiff; mindiff = 255 * 3; for (y = 0; y < source->height; y++) { for (x = 0; x < source->width; x++) { offset = y * source->width * 3 + x * 3; curcolor.b = source->imageData[offset]; curcolor.g = source->imageData[offset + 1]; curcolor.r = source->imageData[offset + 2]; curdiff = colordiff(color, curcolor); if (curdiff < mindiff) { sx = x; sy = y; mindiff = curdiff; } dest->imageData[y * dest->width + x] = 0; } } list_n = newnode(sx, sy); list_r = NULL; int* map = new int[source->width*source->height]; for (int i = 0; i<source->width*source->height; i++) map[i] = 0; map[sy*source->width + sx] = 1; while (list_n != NULL) { sx = list_n->x; sy = list_n->y; pl_push(&list_r, pl_pop(&list_n)); for (dy = -1; dy <= 1; dy++) { for (dx = -1; dx <= 1; dx++) { if (dx == 0 && dy == 0) continue; if (dx != 0 && dy != 0) continue; if (sx + dx == -1 || sx + dx == source->width || sy + dy == -1 || sy + dy == source->height) continue; if (map[(sy + dy)*source->width + sx + dx] == 1) continue; offset = (sy + dy) * source->width * 3 + (sx + dx) * 3; curcolor.b = source->imageData[offset]; curcolor.g = source->imageData[offset + 1]; curcolor.r = source->imageData[offset + 2]; curdiff = colordiff(color, curcolor); if (curdiff <= threshold) { pl_push(&list_n, newnode(sx + dx, sy + dy)); map[(sy + dy)*source->width + sx + dx] = 1; } } } } delete [] map; node_r = list_r; while (node_r != NULL) { dest->imageData[node_r->y * dest->width + node_r->x] = 255; node_r = node_r->next; } dellist(&list_r); }float sum1(std::vector<float>* x, std::vector<float>* y, float yCurr) { float sum = 0; for (int i = 0; i < x->size(); i++) { sum += ((*x)[i] * ((*y)[i] - yCurr)); } return sum / x->size()*-2; }float sum2(std::vector<float>* x, std::vector<float>* y, float yCurr) { float sum = 0; for (int i = 0; i < x->size(); i++) { sum += ((*y)[i] - yCurr); } return sum / x->size()*-2; }void linearRegression(std::vector<float>* x, std::vector<float>* y, int nbData, float& b0, float& b1) { float xave = 0; float yave = 0; for (int i = 0; i < nbData; i++) { xave += (*x)[i]; yave += (*y)[i]; } xave /= (float)nbData; yave /= (float)nbData; float a1 = 0; float a2 = 0; for (int i = 0; i < nbData; i++) { a1 += ((*x)[i] - xave)*((*x)[i] - xave); a2 = a2 + ((*x)[i] - xave)*((*y)[i] - yave); } b1 = a2 / a1; b0 = yave - b1*xave; }void rgrow(Mat *source, Mat *dest, Color color, int threshold) { PosList *list_n; PosList *node_r; PosList *list_r; Color curcolor; int x, y; int sx, sy; int dx, dy; int offset; int mindiff, curdiff; int width = source->cols; int height = source->rows; mindiff = 255 * 3; for (y = 0; y < height; y++) { for (x = 0; x < width; x++) { offset = y * width * 3 + x * 3; curcolor.b = source->data[offset]; curcolor.g = source->data[offset + 1]; curcolor.r = source->data[offset + 2]; curdiff = colordiff(color, curcolor); if (curdiff < mindiff) { sx = x; sy = y; mindiff = curdiff; } dest->data[y * width + x] = 0; } } list_n = newnode(sx, sy); list_r = NULL; int* map = new int[width*height]; for (int i = 0; i<width*height; i++) map[i] = 0; map[sy*width + sx] = 1; while (list_n != NULL) { sx = list_n->x; sy = list_n->y; pl_push(&list_r, pl_pop(&list_n)); for (dy = -1; dy <= 1; dy++) { for (dx = -1; dx <= 1; dx++) { if (dx == 0 && dy == 0) continue; if (dx != 0 && dy != 0) continue; if (sx + dx == -1 || sx + dx == width || sy + dy == -1 || sy + dy == height) continue; if (map[(sy + dy)*width + sx + dx] == 1) continue; offset = (sy + dy) * width * 3 + (sx + dx) * 3; curcolor.b = source->data[offset]; curcolor.g = source->data[offset + 1]; curcolor.r = source->data[offset + 2]; curdiff = colordiff(color, curcolor); if (curdiff <= threshold) { pl_push(&list_n, newnode(sx + dx, sy + dy)); map[(sy + dy)*width + sx + dx] = 1; } } } } delete[] map; node_r = list_r; while (node_r != NULL) { dest->data[node_r->y * width + node_r->x] = 255; node_r = node_r->next; } dellist(&list_r); }void findCenterLine(Mat* img, Vec4i& l) { int imageHeight=img->rows; int imageWidth=img->cols; Mat dist(img->rows, img->cols, CV_8UC1); Mat dist1(img->rows, img->cols, CV_8UC1); distanceTransform(*img, dist, DIST_C, CV_DIST_MASK_PRECISE); normalize(dist, dist, 0.0, 1.0, NORM_MINMAX); std::vector<float> array; if (dist.isContinuous()) { array.assign((float*)dist.datastart, (float*)dist.dataend); } else { for (int i = 0; i < dist.rows; ++i) { array.insert(array.end(), dist.ptr<float>(i), dist.ptr<float>(i) + dist.cols); } } double max = 0; for (int i = 0; i < imageHeight*imageWidth; i++) { if (array[i]>max) { max = array[i]; } } std::vector<float> x; std::vector<float> y; for (int i = 0; i < imageHeight; i++) { for (int j = 0; j < imageWidth; j++) { if (array[i*imageWidth+j]>max*0.1) { dist1.data[i*imageWidth + j]=255; x.push_back((float)j); y.push_back((float)i); } else { dist1.data[i*imageWidth + j] = 0; } } } float b0, b1; linearRegression(&x, &y, x.size(), b0, b1); l[0] = 0; l[1] = b0 + b1*l[0]; if(l[1]<=0) { l[1]=0; l[0]=(l[1]-b0)/b1; } if(l[1]>=imageHeight) { l[1]=imageHeight; l[0]=(l[1]-b0)/b1; } l[2] = imageWidth; l[3] = b0 + b1*l[2]; if(l[3]<=0) { l[3]=0; l[2]=(l[3]-b0)/b1; } if(l[3]>=imageHeight) { l[3]=imageHeight; l[2]=(l[3]-b0)/b1; } imshow("Dist", dist); } int main (void) { int imageWidth = 640; int imageHeight = 480;
raspicam::RaspiCam_Cv Camera; Camera.set( CV_CAP_PROP_FORMAT, CV_8UC3); Camera.set( CV_CAP_PROP_FRAME_WIDTH, imageWidth); Camera.set( CV_CAP_PROP_FRAME_HEIGHT, imageHeight); Mat orgImg; Mat cvEdge; Mat filteredImg(imageHeight, imageWidth, CV_8UC1);
if (!Camera.open()) {cerr<<"Error opening the camera"<<endl;return -1;} while(1) { Camera.grab(); Camera.retrieve(orgImg); CV_Assert(orgImg.data); blur(orgImg, orgImg, Size(10,10)); int threshold = 250; Color color; color.r = 255; color.g = 0; color.b = 0; rgrow(&orgImg, &filteredImg, color, threshold); Canny(orgImg, cvEdge, 10, 10*3, 3); Vec4i lineSeg; findCenterLine(&filteredImg, lineSeg); line(orgImg, Point(lineSeg[0], lineSeg[1]), Point(lineSeg[2], lineSeg[3]), Scalar(255, 0, 255), 3, CV_AA); imshow("Org", orgImg); imshow("Filtered", filteredImg); imshow("Edge", cvEdge); if ( waitKey(20) == 27 )break; } Camera.release(); }
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