Goal: Image filters and edge detectors

• Remove noise by blurring filters: Gaussian, mean and median filters.
• Detect edges by directional filters: sobel and laplacian files.
• Detect edges by Canny detector

Readings and sample codes

• OpenCV 3 computer vision application programming cookbook. R. Laganière, Packt Publishing, 2017. [Book URL]
  • Chapter 6 Filtering the images (PDF, code)
  • Read the README.txt in code for more details of sample codes.
  • You can use the provided sample codes in your homework to practice image filters.
• OpenCV online documentation
  • Image Filtering module: blur(), GaussianBlur(), medianBlur(), filter2D(), Laplacian(), Sobel() functions
  • Feature Detection module: Canny() function
  • Tutorial: OpenCV 3.4.x tutorial on Canny edge detector

Programming

• Write three program codes: denoise.cpp, edge_detection_filter.cpp, and canny_detector.cpp.
• denoise.cpp: write a program code to run Gaussian, Mean, and Median filters for one image.
  • Follow the explanation in this PDF. Remember that you have to change kernel size and compare the blurring results among filters and among kernel sizes.
  • Then you have to add salt-and-pepper noise and run the three filters again. You have to change kernel size and compare the denoise results among filters and among kernel sizes.
• edge_detection.cpp: write a program code to run Sobel and Laplacian filters
  • Follow the explanation in this PDF. Remember that you have to use an image to run both Sobel and Laplacian filters. Compare the results of edge images.
• canny_detector.cpp: write a program code to run the Canny edge detector by OpenCV.

Web Report

• Create a web page with descriptions, explanation and pictures for your programs.
• Requirements of the report page:
  • For each program code, you have to write 4 parts: (1) goal of this code, (2) theory and principle of the code, (3) code segment explanation, and (4) result comparison or analysis.
  • Use your image to run your programs.
  • Change parameters of algorithm's functions to get different result images.
  • Compare and discuss the result images, and explain why the change of parameters can produce different results.
• Submit your web address by Google Classroom.