Ashok Elluswamy's profile - activity

I have a image with about 50 to 100 small contours. I wish to find the average color of each of these contours in real-time (about 25, (960 x 480) pixel images per sec). Some of the ways I could think of was

1. Draw contour with FILLED option for each contour; use each image as a mask over the original image, thus find the average. But I presume that this method won't be real-time at first glance.
2. Study OpenCV implementation of drawContour function and study their implementation of drawContour with the FILLED option. But the code seems really complex and not readily understandable.
3. Calculate the minimum area rectangle, find all the points inside the rectangle using transformation, and find average of points that are non-zero. Again, seems complex approach.

Is there an easier, efficient way to do this?

I'm trying to draw an arbitrary quadrilateral over an image using the polylines function in opencv. When I do I get the following error

OpenCV Error: Assertion failed (p.checkVector(2, CV_32S) >= 0) in polylines, file /tmp/buildd/ros-fuerte-opencv2-2.4.2-1precise-20130312-1306/modules/core/src/d
rawing.cpp, line 2065

I call the function as like so,

cv2.polylines(img, points, 1, (255,255,255))

Where points is as numpy array as shown below (The image size is 1280x960):

[[910 641]
 [206 632]
 [696 488]
 [458 485]]

and img is just a normal image that I'm able to imshow. Currently I'm just drawing lines between these points myself, but I'm looking for a more elegant solution.

How should I correct this error?

BACKGROUND:

I have a a camera mounted on a car facing forward and I want to find the roadmarks. Hence I'm trying to transform the image into a birds eye view image, as viewed from a virtual camera placed 15m in front of the camera and 20m above the ground. I implemented a prototype that uses OpenCV's warpPerspective function. The perspective transformation matrix is got by defining a region of interest on the road and by calculating where the 4 corners of the ROI are projected in both the front and the bird's eye view cameras. I then use these two sets of 4 points and use getPerspectiveTransform function to compute the matrix. This successfully transforms the image into top view.

QUESTION:

When should I undistort the front facing camera image? Should I first undistort and then do this transform or should I first transform and then undistort.

If you are suggesting the first case, then what camera matrix should I use to project the points onto the bird's eye view camera. Currently I use the same raw camera matrix for both the projections.

Please ask more details if my description is confusing!