CV2019Fall

Computer Vision I at NTU 2019 Fall.

Indrocution

This course has 10 homeworks.

Environment

• Programming Language: Python 3
• Programming IDE: Spyder
• Operating System: Windows 10 x64

HW1: Basic Image Manipulation

• Part 1 of this homework is writing a program to generate the following images from lena.bmp.

  • Up-side-down lena.bmp.
  • Right-side-left lena.bmp.
  • Diagonally mirrored lena.bmp.

• Part 2 of this homework is using any kind of software to do the following things:

  • Rotate lena.bmp 45 degrees clockwise.
  • Shrink lena.bmp in half.
  • Binarize lena.bmp at 128 to get a binary image.

• Code

• Report

HW2: Basic Image Manipulation

• Part 1 of this homework is to binarize lena.bmp with threshold 128 (0-127, 128-255).

• Part 2 of this homework is to draw the histogram of lena.bmp.

• Part 3 of this homework is to find connected components with following rules:

  • Draw bounding box of regions.
  • Draw cross at centroid of regions.
  • Omit regions that have a pixel count less than 500.

• Code

• Report

HW3: Histogram Equalization

• This homework is to do histogram equalization with following rules:
  • Do histogram on original lena image.
  • Adjust the brightness of lena.bmp to one-third.
  • Do histogram equalization on dark image.
  • Show the histogram of the final image.
• Code
• Report

HW4: Mathematical Morphology - Binary Morphology

• This homework is to do binary morphology with following rules:

  • Please use the octagonal 3-5-5-5-3 kernel.
  • Please use the “L” shaped kernel to detect the upper-right corner for hit-and-miss transform.
  • Please process the white pixels (operating on white pixels).
  • Five images should be included in your report: Dilation, Erosion, Opening, Closing, and Hit-and-Miss.

• Code

• Report

HW5: Mathematical Morphology - Gray Scaled Morphology

• This homework is to do gray scaled morphology with following rules:

  • Please use the octagonal 3-5-5-5-3 kernel.
  • Please take the local maxima or local minima respectively.
  • Four images should be included in your report: Dilation, Erosion, Opening, and Closing.

• Code

• Report

HW6: Yokoi Connectivity Number

• This homework is to do Yokoi connectivity number with following rules:
  • Please binarize leba.bmp with threshold 128.
  • Please down sampling binary.bmp from 512x512 to 64x64, using 8x8 blocks as unit and take the topmost-left pixel as the down sampling data.
  • Print Yokoi connectivity number to text file.
• Code
• Report

HW7: Thinning

• This homework is to do thinning operation with following rules:
  • Please binarize leba.bmp with threshold 128.
  • Do thinning operation on binary image.
• Code
• Report

HW8: Noise Removal

• This homework is to do noise removal with following rules:
  • Generate Gaussian noise with amplitude of 10 and 30.
  • Generate salt-and-pepper noise with probability of 0.1 and 0.05.
  • Use the 3x3 and 5x5 box filter on noise images.
  • Use the 3x3 and 5x5 median filter on noise images.
  • Use opening-then-closing and closing-then-opening filter on noise images.
  • Calculate the signal-to-noise-ratio (SNR) of noise images.
• Code
• Report

HW9: General Edge Detection

• This homework is to do general edge detection with following rules:
  • Robert’s operator with threshold of 12.
  • Prewitt’s edge detector with threshold of 24.
  • Sobel’s edge detector with threshold of 38.
  • Frei and Chen’s gradient operator with threshold of 30.
  • Kirsch’s compass operator with threshold of 135.
  • Robinson’s compass operator with threshold of 43.
  • Nevatia-Babu 5x5 operator with threshold of 12500.
• Code
• Report

HW10: Zero Crossing Edge Detection

• This homework is to do zero crossing edge detection with following rules:
  • Laplacian mask 1 with threshold of 15.
  • Laplacian mask 2 with threshold of 15.
  • Minimum variance Laplacian with threshold of 20.
  • Laplacian of Gaussian with threshold of 3000.
  • Difference of Gaussian with threshold of 1.
• Code
• Report