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1. Superpixel-based-Fast-Fuzzy-C-Means-Clustering-for-Color-Image-Segmentation Superpixel-based-Fast-Fuzzy-C-Means-Clustering-for-Color-Image-Segmentation Public

   We propose a superpixel-based fast FCM (SFFCM) for color image segmentation. The proposed algorithm is able to achieve color image segmentation with a very low computational cost, yet achieve a hig…

   MATLAB 68 22

2. Significantly-Fast-and-Robust-FCM-Based-on-Morphological-Reconstruction-and-Membership-Filtering Significantly-Fast-and-Robust-FCM-Based-on-Morphological-Reconstruction-and-Membership-Filtering Public

   A fast and robust fuzzy c-means clustering algorithms, namely FRFCM, is proposed. The FRFCM is able to segment grayscale and color images and provides excellent segmentation results.

   MATLAB 32 8

3. Robust-Self-Sparse-Fuzzy-Clustering-for-Image-Segmentation Robust-Self-Sparse-Fuzzy-Clustering-for-Image-Segmentation Public

   Our paper “Robust Self-Sparse Fuzzy Clustering for Image Segmentation” has been accepted for publication in IEEE Access. 2020.

   MATLAB 14 3

4. Adaptive-Morphological-Reconstruction-for-Seeded-Image-Segmentation Adaptive-Morphological-Reconstruction-for-Seeded-Image-Segmentation Public

   In this paper, a novel adaptive morphological reconstruction (AMR) operation is proposed. AMR is able to obtain better seed images to improve the seeded segmentation algorithms.

   MATLAB 12 4

5. Automatic-Fuzzy-Clustering-Framework-for-Image-Segmentation Automatic-Fuzzy-Clustering-Framework-for-Image-Segmentation Public

   We proposed an automatic fuzzy clustering framework (AFCF) for image segmentation which is published in Transactions on Fuzzy Systems, 2020.

   MATLAB 12 5