Image segmentation is a technique in image processing and computer vision where a digital image is partitioned into multiple segments (discrete groups of pixels). The purpose of segmentation is to simplify or change the representation of an image into something that is more meaningful and easier for the computer systems to analyze. The goal of this project is to implement two image segmentation methods, K-Means clustering and Otsu’s Method in C using two of the most widely used application programming interfaces (APIs) for parallel programming, OpenMP and MPI.

This project was conducted for COMP 605 at SDSU taught by Professor Miguel Dumett. Group members: Luna Huynh and Daisy Ulloa