Könyv Clustering Based Image Segmentation for Multi Resolution Images Dr. M. Ganesh

Clustering Based Image Segmentation for Multi Resolution Images

Szerző: Dr. M. Ganesh
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 8-11 napon belül
26 801 Ft
Clustering is a process of classifying objects or patterns in such a way that the samples in the sam...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2023
oldal
204
EAN
9786206159803
ISBN
6206159809
Enbook ID
43510465
Súly
322
Méretek
150 x 220 x 13

Teljes leírás

Clustering is a process of classifying objects or patterns in such a way that the samples in the same group are more similar than the samples in different groups. Based on the fuzzy theory, the fuzzy clustering method, which produces the idea of partial membership of clustering. One of the most important and widely used fuzzy clustering methods is the Fuzzy C-Means (FCM) algorithm. The main purpose of the FCM algorithm is to make the vector space of a sample point be divided into a number of sub-spaces in accordance with a distance measure. However, the FCM algorithm does not take the local spatial property of images into consideration, and hence suffers from high sensitivity to noise.Image segmentation plays a crucial role in many medical imaging applications also. Many algorithms and techniques have been developed to solve image segmentation problems. Spectral pattern is not sufficient in high resolution image for image segmentation due to variability of spectral and structural information.In order to further improve the segmentation performance and convergence speed for gray images corrupted by noise, a kernel version of GFCM with spatial information is proposed.

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