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add close feature

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samilyjcc 2016-06-14 11:36:58 +02:00
parent ff44b1eb13
commit ca53673111
1 changed files with 35 additions and 16 deletions
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51
src/papillon.cpp
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@ -14,7 +14,7 @@ using namespace std;
class Traite_image { class Traite_image {
public: public:
const static int SENSITIVITY_VALUE = 40; const static int SENSITIVITY_VALUE = 40;
const static int BLUR_SIZE = 10; const static int BLUR_SIZE = 15;
Mat prev; Mat prev;
@ -78,7 +78,7 @@ class Traite_image {
searchForMovement(prev_cropped, next_stab_cropped, output); searchForMovement(prev_cropped, next_stab_cropped, output);
pub_img.publish(cv_bridge::CvImage(msg->header, "mono8", output).toImageMsg()); pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
// bridge_input is handled by a smart-pointer. No explicit delete needed. // bridge_input is handled by a smart-pointer. No explicit delete needed.
//droneTracking(Rect(Point(0,0), output.size())); //droneTracking(Rect(Point(0,0), output.size()));
@ -138,8 +138,8 @@ class Traite_image {
cur.copyTo(output); cur.copyTo(output);
cvtColor(prev, prev_grey, COLOR_BGR2GRAY); cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
cvtColor(cur, cur_grey, COLOR_BGR2GRAY); cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
GaussianBlur(prev_grey, prev_grey, Size(15,15), 3.0); GaussianBlur(prev_grey, prev_grey, Size(BLUR_SIZE,BLUR_SIZE), 3.0);
GaussianBlur(cur_grey, cur_grey, Size(15,15), 3.0); GaussianBlur(cur_grey, cur_grey, Size(BLUR_SIZE,BLUR_SIZE), 3.0);
//blur(prev_grey, prev_grey, Size(BLUR_SIZE, BLUR_SIZE)); //blur(prev_grey, prev_grey, Size(BLUR_SIZE, BLUR_SIZE));
//blur(cur_grey, cur_grey, Size(BLUR_SIZE, BLUR_SIZE)); //blur(cur_grey, cur_grey, Size(BLUR_SIZE, BLUR_SIZE));
@ -149,15 +149,30 @@ class Traite_image {
// threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY); // threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
// // Blur to eliminate noise // // Blur to eliminate noise
// blur(thres, thres, Size(BLUR_SIZE, BLUR_SIZE)); // blur(thres, thres, Size(BLUR_SIZE, BLUR_SIZE));
// threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY); threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
thres.copyTo(output);
//~ int dilation_size = 2;
//~ Mat element = getStructuringElement( MORPH_ELLIPSE,
//~ Size( 2*dilation_size + 1, 2*dilation_size+1 ),
//~ Point( dilation_size, dilation_size ) );
//~ // Apply the dilation operation
//~ Mat dilated_thres;
//~ dilate(thres, dilated_thres, element );
//~
//~ dilated_thres.copyTo(output);
Mat closed_thres;
Mat structuringElement = getStructuringElement(MORPH_ELLIPSE, Size(40, 40));
morphologyEx( thres, closed_thres, MORPH_CLOSE, structuringElement );
//closed_thres.copyTo(output);
//notice how we use the '&' operator for objectDetected and output. This is because we wish //notice how we use the '&' operator for objectDetected and output. This is because we wish
//to take the values passed into the function and manipulate them, rather than just working with a copy. //to take the values passed into the function and manipulate them, rather than just working with a copy.
//eg. we draw to the output to be displayed in the main() function. //eg. we draw to the output to be displayed in the main() function.
bool objectDetected = false; bool objectDetected = false;
Mat temp; Mat temp;
thres.copyTo(temp); closed_thres.copyTo(temp);
//these two vectors needed for output of findContours //these two vectors needed for output of findContours
vector< vector<Point> > contours; vector< vector<Point> > contours;
vector<Vec4i> hierarchy; vector<Vec4i> hierarchy;
@ -172,23 +187,27 @@ class Traite_image {
if(objectDetected){ if(objectDetected){
//the largest contour is found at the end of the contours vector //the largest contour is found at the end of the contours vector
//we will simply assume that the biggest contour is the object we are looking for. //we will simply assume that the biggest contour is the object we are looking for.
vector< vector<Point> > largestContourVec; //vector< vector<Point> > largestContourVec;
largestContourVec.push_back(contours.at(contours.size()-1)); //largestContourVec.push_back(contours.at(contours.size()-1));
//make a bounding rectangle around the largest contour then find its centroid //make a bounding rectangle around the largest contour then find its centroid
//this will be the object's final estimated position. //this will be the object's final estimated position.
objectBoundingRectangle = boundingRect(largestContourVec.at(0)); for(int i=0; i<contours.size();i++)
{
objectBoundingRectangle = boundingRect(contours[i]);
rectangle(output, objectBoundingRectangle, Scalar(0, 255, 0), 2);
}
} }
//make some temp x and y variables so we dont have to type out so much //make some temp x and y variables so we dont have to type out so much
int x = objectBoundingRectangle.x; //~ int x = objectBoundingRectangle.x;
int y = objectBoundingRectangle.y; //~ int y = objectBoundingRectangle.y;
int width = objectBoundingRectangle.width; //~ int width = objectBoundingRectangle.width;
int height = objectBoundingRectangle.height; //~ int height = objectBoundingRectangle.height;
//draw a rectangle around the object //draw a rectangle around the object
rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2); //rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2);
//write the position of the object to the screen //write the position of the object to the screen
putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2); //putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
} }
inline bool isFlowCorrect(Point2f u) inline bool isFlowCorrect(Point2f u)