# Revision history [back]

### Check if convexhull has parallel lines

I have a simple program that finds convex hulls and draws them onto my frame.

For my application, I am interested in one convex hull in particular shown below inside the labels S and V.

One way I thought of narrowing it down is looking for convex hulls which consist of parallel lines by performing a theta test for parallelism.

The structure returned by convexHull is of vector<vector<Point>>. Below is a sample image showing the points of one convex inside the container

My questions are:

1. Are the points returned in the order of (634, 599)->(387, 599)->....->(634, 597)->(634, 599)? If no, what is the order then?
2. Along with parallelism, length is another factor I had in mind to filter out useless convexes. Any better suggestions to detect this structure?

Any recommendations/responses are highly appreciated it!

### Check if convexhull has parallel lines

I have a simple program that finds convex hulls and draws them onto my frame.

For my application, I am interested in one convex hull in particular shown below inside the labels S and V.

One way I thought of narrowing it down is looking for convex hulls which consist of parallel lines by performing a theta test for parallelism.

The structure returned by convexHull is of vector<vector<Point>>. Below is a sample image showing the points of one convex inside the container

My questions are:

1. Are the points returned in the order of Is (634, 599)->(387, 599)->....->(634, 597)->(634, 599)? the relation between the points? If no, what is the order then?
2. Along with parallelism, length is another factor I had in mind to filter out useless convexes. Any better suggestions to detect this structure?

Any recommendations/responses are highly appreciated it!

### Check if convexhull has parallel lines

I have a simple program that finds convex hulls and draws them onto my frame.

For my application, I am interested in one convex hull in particular shown below inside the labels S and V.

One way I thought of narrowing it down is looking for convex hulls which consist of parallel lines by performing a theta test for parallelism.

The structure returned by convexHull is of vector<vector<Point>>. Below is a sample image showing the points of one convex inside the container

My questions are:

1. Is (634, 599)->(387, 599)->....->(634, 597)->(634, 599) the relation between the points? If no, what is then?
2. Along with parallelism, length is another factor I had in mind to filter out useless convexes. Any better suggestions to detect this structure?

Any recommendations/responses are highly appreciated it!

Edit 1

Sample Image

Minimal Code

int main(int argc, const char * argv[])
{
Mat frame, grey, threshold, cannyEdge, gaussianBlur;
vector<vector<Point>> contours;

VideoCapture camera(0);

if(!camera.isOpened())
{
cerr << "Error grabbing the camera\n";
return -1;
}

while(true)
{

cvtColor(frame, grey, COLOR_BGR2GRAY);

for(int mainIndex = 0; mainIndex <= 12; ++mainIndex)
{
int autoThreshold = 200 - 15 * mainIndex;

// TODO: tweak these values around
Canny(grey, cannyEdge, 25, 2*autoThreshold, 3, true);
GaussianBlur(cannyEdge, gaussianBlur, Size(3,3), 0);
findContours(gaussianBlur, contours, hierarchy, CV_RETR_LIST, CHAIN_APPROX_SIMPLE);

Mat contoursFrame = Mat::zeros(frame.size(), CV_8UC3);
Mat convexHullFrame = Mat::zeros(frame.size(), CV_8UC3);

convexes.resize(contours.size());

for(size_t index = 0; index < contours.size(); ++index)
{
convexHull(contours[index], convexes[index]);
}

cout << "Found " << thresholdCentres.size() << " circles at threshold " << autoThreshold << endl;

for(size_t index = 0; index < contours.size(); ++index)
{
Scalar colour = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
drawContours(contoursFrame, contours, int(index), colour, 2, LINE_8);
drawContours(convexHullFrame, convexes, int(index), colour, 2, LINE_8);
}

imshow("Convex", convexHullFrame);
imshow("Contours", contoursFrame);
}

char tappedKey = waitKey(1);

if(tappedKey == 27)
{
break;
}
}

destroyAllWindows();

camera.release();

return 0;
}


### Check if convexhull has parallel lines

I have a simple program that finds convex hulls and draws them onto my frame.

For my application, I am interested in one convex hull in particular shown below inside the labels S and V.

One way I thought of narrowing it down is looking for convex hulls which consist of parallel lines by performing a theta test for parallelism.

The structure returned by convexHull is of vector<vector<Point>>. Below is a sample image showing the points of one convex inside the container

My questions are:

1. Is (634, 599)->(387, 599)->....->(634, 597)->(634, 599) the relation between the points? If no, what is then?
2. Along with parallelism, length is another factor I had in mind to filter out useless convexes. Any better suggestions to detect this structure?

Any recommendations/responses are highly appreciated it!

Edit 1

Sample Image

Minimal Code

int main(int argc, const char * argv[])
{
Mat frame, grey, threshold, cannyEdge, gaussianBlur;
vector<vector<Point>> contours;

VideoCapture camera(0);

if(!camera.isOpened())
{
cerr << "Error grabbing the camera\n";
return -1;
}

while(true)
{

cvtColor(frame, grey, COLOR_BGR2GRAY);

for(int mainIndex = 0; mainIndex <= 12; ++mainIndex)
{
int autoThreshold = 200 - 15 * mainIndex;

// TODO: tweak these values around
Canny(grey, cannyEdge, 25, 2*autoThreshold, 3, true);
GaussianBlur(cannyEdge, gaussianBlur, Size(3,3), 0);
findContours(gaussianBlur, contours, hierarchy, CV_RETR_LIST, CHAIN_APPROX_SIMPLE);

Mat contoursFrame = Mat::zeros(frame.size(), CV_8UC3);
Mat convexHullFrame = Mat::zeros(frame.size(), CV_8UC3);

convexes.resize(contours.size());

for(size_t index = 0; index < contours.size(); ++index)
{
convexHull(contours[index], convexes[index]);
}

cout << "Found " << thresholdCentres.size() << " circles at threshold " << autoThreshold << endl;

for(size_t index = 0; index < contours.size(); ++index)
{
Scalar colour = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
drawContours(contoursFrame, contours, int(index), colour, 2, LINE_8);
drawContours(convexHullFrame, convexes, int(index), colour, 2, LINE_8);
}

imshow("Convex", convexHullFrame);
imshow("Contours", contoursFrame);
}

char tappedKey = waitKey(1);

if(tappedKey == 27)
{
break;
}
}

destroyAllWindows();

camera.release();

return 0;
}