Explain K-means clustering methods with the help of a suitable example

Question

Explain K-means clustering methods with the help of a suitable example. Also, discuss the advantages and disadvantages of k -means clustering methods.

25 Jul 2024

Answer :

Word Count : 348

K-means Clustering in Digital Image Processing and Computer Vision

K-means clustering is a widely used method in digital image processing and computer vision for partitioning an image into distinct regions or segments. The algorithm works by grouping similar pixels based on their features, such as color or intensity, into \( k \) clusters. Here's a step-by-step explanation using an example:

Example: Image Segmentation

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