Automatic thresholding of gray-level pictures using two-dimensional entropy
Computer Vision, Graphics, and Image Processing
Quantitative evaluation of color image segmentation results
Pattern Recognition Letters
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Multiresolution Color Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering binary data streams with K-means
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
An Adaptive Fuzzy Clustering Algorithm for Medical Image Segmentation
MIAR '01 Proceedings of the International Workshop on Medical Imaging and Augmented Reality (MIAR '01)
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Multilevel thresholding for image segmentation through a fast statistical recursive algorithm
Pattern Recognition Letters
Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
Java-ML: A Machine Learning Library
The Journal of Machine Learning Research
Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Medical Image Segmentation Using Improved Mountain Clustering Technique Version-2
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
Likelihood based hierarchical clustering
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Red-eye detection and correction using inpainting in digital photographs
IEEE Transactions on Consumer Electronics
Fine edge-preserving deinterlacing algorithm for progressive display
IEEE Transactions on Consumer Electronics
Adaptive fuzzy-K-means clustering algorithm for image segmentation
IEEE Transactions on Consumer Electronics
A recursive thresholding technique for image segmentation
IEEE Transactions on Image Processing
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This paper introduces modified versions of the K-Means (KM) and Moving K-Means (MKM) clustering algorithms, called the Two-Dimensional K-Means (2D-KM) and Two-Dimensional Moving K-Means (2D-MKM) algorithms respectively. The performances of these two proposed algorithms are compared with three of the commonly used conventional clustering algorithms, namely K-Means (KM), Fuzzy C-Means (FCM), and Moving K-Means (MKM). The new algorithms incorporate the median value of considered pixel intensity with its neighboring pixel; together with the pixel's own intensity for the assigning process of the pixel to the nearest cluster. From the observed qualitative and quantitative results, it is proven that 2D-KM and 2D-MKM perform better than KM, FCM, and MKM in terms of producing more homogeneous segmentation results, while taking shorter time in executing the process as compared to FCM.