An efficient approach for optimal multilevel thresholding selection for gray scale images based on improved differential search algorithm

被引：26

作者：

Kotte, Sowjanya ^{[1
]}

Kumar, P. Rajesh ^{[1
]}

Injeti, Satish Kumar ^{[2
]}

机构：

[1] Andhra Univ, Coll Engn A, Dept Elect & Commun Engn, Visakhapatnam 530003, Andhra Pradesh, India

[2] GMR Inst Technol, Dept Elect & Elect Engn, Rajam 532127, Andhra Pradesh, India

来源：

AIN SHAMS ENGINEERING JOURNAL | 2018年 / 9卷 / 04期

关键词：

Multilevel thresholding; Gray scale image segmentation; Improved differential search algorithm; Quantitative and qualitative analysis; OPTIMIZATION; SEGMENTATION;

D O I：

10.1016/j.asej.2016.06.007

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Segmentation is one of the important steps for image analysis. Multilevel thresholding image segmentation was more popular in image segmentation. Otsu and Kapur based methods are most popular for multilevel threshold image segmentation. Many authors implemented evolutionary algorithms for the optimal multilevel threshold selection based on the above methods. In this paper, an efficient approach for multilevel image segmentation has been proposed and implemented based on novel evolutionary algorithm Improved Differential Search (IDS). The feasibility of proposed approach/algorithm has been tested on standard gray scale images. To check the effectiveness of the proposed approach/algorithm, all experimental results are analyzed quantitatively and qualitatively. (C) 2016 Ain Shams University.

引用

页码：1043 / 1067

页数：25

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