Learning OpenCV

Exercises

1. Neglecting image noise, does the IPAN algorithm return the same "dominant points" as we zoom in on an object? As we rotate the object?

   1. Give the reasons for your answer.

   2. Try it! Use PowerPoint or a similar program to draw an "interesting" white shape on a black background. Turn it into an image and save. Resize the object several times, saving each time, and reposition it via several different rotations. Read it in to OpenCV, turn it into grayscale, threshold, and find the contour. Then use cvFindDominantPoints() to find the dominant points of the rotated and scaled versions of the object. Are the same points found or not?

2. Finding the extremal points (i.e., the two points that are farthest apart) in a closed contour of N points can be accomplished by comparing the distance of each point to every other point.

   1. What is the complexity of such an algorithm?

   2. Explain how you can do this faster.

3. Create a circular image queue using CvSeq functions.

4. What is the maximal closed contour length that could fit into a 4-by-4 image? What is its contour area?

5. Using PowerPoint or a similar program, draw a white circle of radius 20 on a black background (the circle's circumference will thus be 2 π 20 ≈ 125.7. Save your drawing as an image.

   1. Read the image in, turn it into grayscale, threshold, and find the contour. What is the contour length? Is it the same (within rounding) or different from the calculated length?

   2. Using 125.7 as a base length of the contour, run cvApproxPoly() using as parameters ...