Retrieval of Near Duplicate Images using K means and PSO Clustering

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

vessel segmentation in retinal images using multi-scale line operator and k-means clustering

detecting blood vessels is an important task in retinal image analysis.  the task is more challenging with the presence of bright and dark lesions in retinal images. here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. first, the negative impact of bright lesions is reduced by using k-means segmentation in a perceptive sp...

OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM

This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...

Document Clustering Analysis Based on Hybrid PSO+K-means Algorithm

There is a tremendous proliferation in the amount of information available on the largest shared information source, the World Wide Web. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize and organize the information. Recent studies have shown that partitional clustering algorithms are more suitable for clustering larg...

Canonical PSO Based K-Means Clustering Approach for Real Datasets

"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different ...