Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means 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...

segmentation of photospheric solar images by using c-means,k-means, and fcm algorithms

Evaluation of Segmentation in Magnetic Resonance Images Using k-Means and Fuzzy c-Means Clustering Algorithms

The purpose of cluster analysis is to partition a data set into a number of disjoint groups or clusters. Members within a cluster are more similar to each other than to members from different clusters. Applicability of the centroid-based k-means and representative object-based fuzzy c-means algorithms for study of the Magnetic Resonance Images is analysed in the work. The two algorithms are imp...

Texture Segmentation by using Haar Wavelets and K-means Algorithm

In this paper we focus on image segmentation by proposing a new algorithm based on Haar wavelet decomposition and Kmeans algorithm. When Haar wavelet decomposition is applied to an image it gives an idea about high frequency components. If higher levels of decomposition are performed, different texture region information can be captured. The paper deals with the texture segmentation of an image...