RI UFLA (Universidade Federal de Lavras) >
Revistas UFLA >
Please use this identifier to cite or link to this item:
|Title: ||Multilevel thresholding based on fuzzy C partition and gravitational search algorithm|
|???metadata.dc.creator???: ||Gupta, Chhavi|
|Keywords: ||Fuzzy C partition|
Partição C difusa
Segmentação de imagens
|Publisher: ||Editora da UFLA|
|Citation: ||GUPTA, C.; JAIN, S. Multilevel thresholding based on fuzzy C partition and gravitational search algorithm. INFOCOMP: Journal of Computer Science, Lavras, v. 13, n. 1, p. 1-11, June 2014.|
|Abstract: ||Entropy based image thresholding methods are widely adopted for multilevel image segmentation. Bilevel thresholding partitions an image into two classes, whereas multilevel thresholding partitions an image into multiple classes depending upon thresholding level . The automatic selection of optimal threshold is often treated as an optimization problem. This paper contributes to novel thresholding method, that is based on entropy of fuzzy c partition and gravitational search algorithm (GSA). Experiments have been evaluated on the different test images and results were assessed by entropy, stability, computation time and peak signal to noise ratio (PSNR). The analysis of results conveys that the GSA outperform particle swarm optimization (PSO).|
|Other Identifiers: ||http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/3|
|Appears in Collections:||Infocomp|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.