Programming Question

Description

Programming Assignment: K-means Clustering

Total points: 100

Note: This assignment is for each individual student to complete on his or her own.

In this assignment, you will implement k-means clustering to achieve image compression. To get started, you will need to download the starter code and unzip its contents to the directory where you wish to complete the assignment.

The problem considered in this assignment is to compress the image downloaded from https://leafyplace.com/types-of-birds/

You are required the complete the following steps:

• Implement the K-means Clustering algorithm to group pixels into K clusters. Pixels with similar RGB values fall into the same cluster.
• Plot a graph to show the change of SSE (sum of squared error). Use SSE to determine whether the algorithm converges or not.
• Construct the compressed image.

To get started, open the main script assignmentClustering.m and fill out the missing code blocks.

You can download Matlab by following the instructions provided in this link: https://library.sdsu.edu/computers-technology/software/matlab

What to submit?

A zip file that includes the following items:

• All codes (75 points)
  • Part 1: Load Image (10 points)
  • Part 2: Cluster pixels with K-means (50 points)
  • Part 3: Construct the compressed image (15 points)
• A report that includes (25 points):
  • (20 points) Graph of SSE and compressed images when K = 5, 10, 20 (15 points). Explain the impact of K (5 points).
  • (5 points) Describe what have gone well and what have not gone well during the implementation. Also describe how your current implementation can be potentially improved to achieve better performance.