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)

  • OpenCV 4 Computer Vision Application Programming Cookbook, by D. M. Escrivá, R. Laganiere, Fourth Edition, Packt Publishing, 2019. [Book URL] [GitHub]

    • Chapter 6 Filtering the images (PDF, code)

  • 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.