Geodesic
Application of Grid-based K-means Clustering Algorithm for Optimal Image Processing
Computer Science and Information Systems, Tome 9 (2012) no. 4.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

The effectiveness of K-means clustering algorithm for image segmentation has been proven in many studies, but is limited in the following problems: 1) the determination of a proper number of clusters. If the number of clusters is determined incorrectly, a good-quality segmented image cannot be guaranteed; 2) the poor typicality of clustering prototypes; and 3) the determination of an optimal number of pixels. The number of pixels plays an important role in any image processing, but so far there is no general and efficient method to determine the optimal number of pixels. In this paper, a grid-based K-means algorithm is proposed for image segmentation. The advantages of the proposed algorithm over the existing K-means algorithm have been validated by some benchmark datasets. In addition, we further analyze the basic characteristics of the algorithm and propose a general index based on maximizing grey differences between investigated objective grays and background grays. Without any additional condition, the proposed index is robust in identifying an optimal number of pixels. Our experiments have validated the effectiveness of the proposed index by the image results that are consistent with the visual perception of the datasets.
Keywords: electrical tomography; number of pixels; image ronconstruction 
@article{CSIS_2012_9_4_a16,
     author = {Tingna Shi and Penglong Wang and Jeenshing Wangb and Shihong Yue},
     title = {Application of {Grid-based} {K-means} {Clustering} {Algorithm} for {Optimal} {Image} {Processing}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {9},
     number = {4},
     year = {2012},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a16/}
}
TY  - JOUR
AU  - Tingna Shi
AU  - Penglong Wang
AU  - Jeenshing Wangb
AU  - Shihong Yue
TI  - Application of Grid-based K-means Clustering Algorithm for Optimal Image Processing
JO  - Computer Science and Information Systems
PY  - 2012
VL  - 9
IS  - 4
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a16/
ID  - CSIS_2012_9_4_a16
ER  - 
%0 Journal Article
%A Tingna Shi
%A Penglong Wang
%A Jeenshing Wangb
%A Shihong Yue
%T Application of Grid-based K-means Clustering Algorithm for Optimal Image Processing
%J Computer Science and Information Systems
%D 2012
%V 9
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a16/
%F CSIS_2012_9_4_a16
Tingna Shi; Penglong Wang; Jeenshing Wangb; Shihong Yue. Application of Grid-based K-means Clustering Algorithm for Optimal Image Processing. Computer Science and Information Systems, Tome 9 (2012) no. 4. http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a16/