Part 1 - Harris Corners (60 points): Write a program that loads an image, extracts Harris Corners using the algorithm discussed in class, and displays the corners overlaid on the image. Your program may not make use of any existing functions/code that extract features. Start by using the checkerboard image to test your code. Part 2 - Ranking Corners (20 points): After you've assigned "cornerness" measurements to every pixelFind the max "cornerness" measurement in the image. Label all pixels whose "cornerness" is greater than a certain percentage of this value (i.e. 10%) as corners. The exact percentage you use will probably change based on the image. Bonus #1 (10 points): Additionally, rank corners using the following method and compare the two methods. Divide the image into m blocks. Label the n pixels in each block with the highest "cornerness" values as corners. Play with the parameters (m, n). For both methods you'll probably use different parameter values for different images to get good corners. Bonus #2 (10 points): Visualize the range of "cornerness" values computed for an image. Color pixels with the lowest cornerness value black and pixels with the highest value white. Linearly interpolate between these two values so that other pixels are different shades of gray.

9th Edition

ISBN:9781337669405

Author:FARRELL

Publisher:FARRELL

Chapter6: Arrays

Section: Chapter Questions

Problem 5GZ

Related questions

Question

Create empty images for Ix, Iy, Ixx, Iyy, and Ixy (all the same dimensions as your original image)
Loop through pixels of image and fill in values for Ix, Iy, Ixx, Iyy, and Ixy (ignore the edges when you set up the range of your loops)
Create empty image to hold "cornerness" values
Loop through pixels of image
- Access the a neighborhood surrounding each pixel (start with a 3x3, you can expand it later if you'd like)
  - Sum up all the Ixx, Iyy, and Ixy values in this neighborhood
  - Compute the determinant of the M matrix
  - Compute the trace of the M matrix
  - Compute the "cornerness" value for the center pixel - store in the "cornerness" image
Find max cornerness value in image
set threshold = 0.01(max C value)
loop through pixels. if(C at pixel) > threshold: cv2.circle(image(X,Y),size(b,g,r) - 1)