Machine Vision & Imaging Techniques in Mechanical Engineering

1. Colors in image Lena.bmp. 

a. Plot and observe the three components of the image.

b. Write your own code (not using the built-in function) to convert the image to a grayscale one.

2. Downsampling of image Pepper.bmp

a. Divide the image into blocks with each block of 2×2 pixels. Replace each block by the average intensity of the block.

b. Repeat the work for block sizes of 4×4, 8×8, and 16×16.

3. FFTs of images.

a. Write your own code to create the following grayscale images in a 128×128 array. The images should make full use of the 0 to 1 range (or 0 to 255 scales depending on your code) except the first image.

i. Constant value of 0.5. ["const"]

ii. Ramp from 0 to 1 in one direction and constant in another direction. ["ramp"]

iii. Cosine signal with 4 periods in one direction and constant in another direction. ["cosine4"]

iv. Cosine signal with 2 periods in both directions. ["cosine2"]

v. Cosine signal with 3 periods in one direction and a ramp function in another direction. ["cosine3"]

b. Use Matlab to do 2D FFT on each of the above six images. Output the magnitude of the FFT results as images.

4. Enhancement of image Boat.bmp

a. Please use an appropriate filtering function to enhance the image.

5. Enhancement of images Caves.jpg and Clouds.jpg

a. One image is too dark and the other is too bright. Please enhance the images by using an appropriate Matlab function.

6. Restoration of images Motion_blur.jpg and Out_of_focus.jpg

a. Please restore the images by using an appropriate Matlab function.

Assignment link - https://www.dropbox.com/s/pewqshz7oylv26w/Assignment.rar?dl=0.