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This project implements and compares the results of 3 different FCM clustering algorithms for image segmentation

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rskarp/fcm-image-segmentation

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FCM for Image Segmentation

The goal of this project, conducted in the Fall 2022 semester of EN.525.770: Intelligent Algorithms at Johns Hopkins University Engineering for Professionals Program, was to identify a published paper on an application of intelligent algorithms and attempt to replicate the results of the paper.

The paper that I selected was "Central Perturbation-based Interval Type-2 Fuzzy C-Means Clustering for Image Segmentation" (Rong et al, 2022). I replicated the paper results by implementing three different variations of fuzzy c-means clustering algorithms, and applied them to 5 generated graphical datasets and 5 images from the Berkley Segmentation Dataset. An example for one image can be seen below, and the full results can be seen in the RKarp_Final Presentation.pdf slides.

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This project implements and compares the results of 3 different FCM clustering algorithms for image segmentation

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