Video: Solar Storms

Now that we have eliminated scaling from our rotation images, we can now try to track/follow our region of interest (ROI) throughout all rotations. Below is the first initial attempt, we marked our first ROI so we know the left most point of the rectangle as well as its dimensions (width and height). So we then derived the new left most point of the shifted rectangle.
The GREEN box is the one that I initially marked, and the BLUE boxes are the ones that are derived from the original marked ROI and the shift in angle rotation. So it is supposed to track the ROI through all rotations. As you can see this is not handled quite right. The upper left hand corner of the box which is always the starting point of cvRect structure, does in fact follow the shift position at each rotation but the actual area of the rectangle is wrong. For example when we get to about degree rotation 90, the box should be inverted, as to cover the area but it still assumes a top down orientation from our rotation point.

In order to overcome this problem a rotation on the derived rectangle would be necessary. OpenCV does not draw rectangles at a rotation, so instead of needing just one point, width and height to describe an upright rectangle, we need to know all the points in the rotated rectangle.

//Get the distance from the center to our point of interest
int a = x - src_center.x;
int b = y - src_center.y;
double distance = sqrt((double)((a*a) + (b*b)));

//Convert the angle to radians
double radians = angle * (PI/180);

//Get the deltas (changes) in our x and y coordinate from our formula above
float deltaX = cos(radians) * a + sin(radians) * b;
float deltaY = cos(radians) * b - sin(radians) * a;

//Add the delta (change) values to our initial point value to get the shift and new coordinates
float newXPos = src_center.x + deltaX;
float newYPos = src_center.y + deltaY;

//Get the rotated rectangle values, from our ROI rotated at a angle value
cv::RotatedRect rect = RotatedRect(cvPoint((newXPos + (widthOfROI/2)), (newYPos + (heightOfROI/2))), Size2f(widthOfROI, heightOfROI), abs(angle));

//Create a holder for 4 points of our rotated rectangle.
CvPoint2D32f box_vtx[4];
cvBoxPoints(rect, box_vtx);

Once you have your 4 points in your rotated rectangle all you then need to do is loop through each point and draw a line connecting each one together, which results in a box drawn on your image. In the below video clip the GREEN box is our initial marked ROI, the BLUE box is our initial tracking implementation that assumed a top down orientation from the top left most corner point that we referenced and the YELLOW box is the new implementation that includes rotating the derived ROI (BLUE box) based on the anchored point in the upper left most corner, which you will notice the BLUE and YELLOW are always anchored at the same point in all rotations.

Tags: image processing, media, opencv, solar cavity

So initially we thought to rotate the image 1 degree and save the resulting image, we then ended up with about 360 image files derived from a single image. If we marked just the initial image (non-rotated) then based off of the placement in that image we could derive the position of interest in all subsequent images. With this technique there were a few problems encountered.
Below is an example of the images and their rotation. You will notice that along with the rotation there was also significant scaling to the image. So not only would we have to derive the position from the rotation but also the scaling.

So, I decided to simplify the situation and alleviate the scaling portion and only focus on the rotation. Below is a code excerpt that rotates an image about the center point and also keeps the original scale. Which is fortunate in our case that our images do not contain any useful information on the edges of the frame so if we lose the edges it does not hurt our purposes at all since its just black space.

//!****************************************************************
//! @details
//! This method rotates an image by a angle (degree) value
//! 
//! @param [in,out] const Mat& source
//! The Mat image to rotate
//!
//! @param [in] double angle
//! The angle (degree) of rotation
//!
//! @return Mat dst
//! The resultant destination image after rotation
//!****************************************************************
Mat RotateImage(const Mat& source, double angle)
{
   //Get the center point of the image
	Point2f src_center(source.cols/2.0F, source.rows/2.0F);
	Mat rotation_matrix = getRotationMatrix2D(src_center, angle, 1.0);

//Show the rotation matrix
//cvNamedWindow( "Rotation Matrix", CV_WINDOW_NORMAL );
//imshow("Rotation Matrix", rotation_matrix);
//waitKey(0);
//cvDestroyWindow("Rotation Matrix");

	Mat dst;
	warpAffine(source, dst, rotation_matrix, source.size());
	return dst;
}

Below is an example of the images and their rotation. You will notice that along with the rotation there was no significant scaling to the image. So we no longer have to derive the position of the region based on the rotation and scaling.

Tags: image processing, media, opencv, solar cavity