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The purpose of this homework is to experiment with edge detection and openCV
Your program should be able to do the following:

1. Edge Detection [5 points]

o Add edge detection for grey level images to your choice of options.
o Use Sobel operator (3by3) and (5×5) to compute dx and dy, compute gradient amplitude, compute edge

o Your program should
 operate within specified ROIs (up to three ROIs as in previous assignments)
 generate display of the amplitude of the gradient operator as intensity image
 generate binary edge image derived from amplitude of the gradient operator by thresholding.
 generate binary edge image by further thresholding the above output using direction information
(e.g. display only horizontal (+/- 10 degree) edges or 45 degree +/- 10 degree edges etc)
o Test your program on some grey level images

2. Utilization of OpenCV [5 points]

o replicate first part of this assignment using OpenCV calls and compare performance
o utilize Canny module of OpenCV and compare to Sobel results
o implement histogram equalization using OpenCV and compare to you histogram stretching

o Implement Otsu algorithm using OpenCV and compare to your optimal thresholding algorithm
o Combine operations by applying histogram equalization only to foreground as determined by Otsu.
 Make sure that you have complete report for this assignment (not just few comments).

 Include input and output images (use several gray level images as appropriate).
 Discuss performance of edge detection on grey level images.
 Discuss performance and utility of OpenCV
 Discuss performance of Canny edge detector (vs Sobel) as edge detection.
 Discuss performance of combined operations

How to submit
• Submit paper report in class on the due date
• See TA help desk for instruction on program submission and testing.