Lab -1
Questions
- Read an image into a variable
- Display that image
- Convert the image into a grayscale image
- Check the height and width of that image
- Extract the RGB channels of a given colour image
- To extract given 100 pixels from a grayscale image
- Create a new image with every 10th pixel horizontally and 20th pixel vertically.
- Flip the image vertically
- Draw the histogram plot of pixel values.
Lab -2
Questions
- Perform translation, scaling and rotation on an image
- In a coloured image perform affine transformation
- In a coloured image extract all R,B and G Perform smoothing (moving avg) on a given image. In one case pad rows and columns. In 2nd case dont allow any extra rows or columns, i.e. do padding in such a way
- Perform gaussian and compare w moving avg by extracting a small patch
- Perform median filter on an image
- If we increase the dimension of a filter, how will it impact the output image?
Lab - 3
Questions
- Apply the prewitt and sobel filters on random image (that have fews edges), and compare the result with original image.
- Increase the weight at positions [x,y+1], [x+1,y], [x-1,y], [x, y-1] in 3*3 sobel filter, and infer how it will impact the edge image concerning the benchmark sobel.
- Apply the LOG filter on the same image that you have taken in Q2, and compare the edge results with output of Q2.
Lab -4
Questions
- Take a patch of size 5*5 with random intensity values. Apply the x-kernel [-1,0,1] and y-kernel [-1,0,1]^T to get the first order gradient in both the dimensions.
- Compute the Harris matrix from these computed gradients.
- Compute the Eigen values and the Eigen vectors for the computed Harris matrix.
- Based on the computed Eigen values of the Harris matrix, identify whether the output patch is, an edge, a corner, or a flat surface.