2015
DOI: 10.1007/s00500-015-1677-6
|View full text |Cite
|
Sign up to set email alerts
|

Multilevel threshold selection for image segmentation using soft computing techniques

Abstract: Multilevel thresholding is the method applied to segment the given image into unique sub-regions when the gray value distribution of the pixels is not distinct. The segmentation results are affected by factors such as number of threshold and threshold values. Hence, this paper proposes different methods for determining optimal thresholds using optimization techniques namely GA, PSO and hybrid model. Parallel algorithms are also proposed and implemented for these methods to reduce the execution time. From the e… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
10
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
4
2

Relationship

0
6

Authors

Journals

citations
Cited by 34 publications
(10 citation statements)
references
References 22 publications
0
10
0
Order By: Relevance
“…Image segmentation is a process of grouping the pixels of an image on the basis of a set of criteria, such as intensity, color, and texture. 22 Threshold segmentation can be regarded as the most straightforward method for image segmentation and is one of the most critical and efficient techniques in image segmentation that is based on area image segmentation in arithmetic. 23 To extract the desired part from an image, the gray value of each pixel in the image is compared with the selected threshold, and a corresponding judgment is made.…”
Section: Adaptive Threshold Segmentationmentioning
confidence: 99%
“…Image segmentation is a process of grouping the pixels of an image on the basis of a set of criteria, such as intensity, color, and texture. 22 Threshold segmentation can be regarded as the most straightforward method for image segmentation and is one of the most critical and efficient techniques in image segmentation that is based on area image segmentation in arithmetic. 23 To extract the desired part from an image, the gray value of each pixel in the image is compared with the selected threshold, and a corresponding judgment is made.…”
Section: Adaptive Threshold Segmentationmentioning
confidence: 99%
“…In remote sensing image segmentation, bi-level thresholding does not give appropriate performance, and there are strong requirements of multilevel thresholding [ 53 ]. Therefore, numerous studies have been reported [ 47 , 53 , 54 , 55 , 56 , 57 , 58 ] in multilevel thresholding.…”
Section: Dg-pso Based Remote Sensing Image Segmentationmentioning
confidence: 99%
“…The most popular way [ 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ] to search the optimal thresholds is to maximize some discriminating criteria (fitness function). The traditional method searches the optimal thresholds using exhaustive search strategies, which lead to high computation costs.…”
Section: Dg-pso Based Remote Sensing Image Segmentationmentioning
confidence: 99%
See 1 more Smart Citation
“…The tenth paper named Multilevel Threshold Selection for Image Segmentation using Soft Computing Techniques by Mala and Sridevi (2015) considered that multilevel thresholding is a method which can be applied to segment a given image into unique sub-regions when gray value distribution of the pixels is not distinct. The segmentation results are affected by factors such as number of threshold and threshold values.…”
mentioning
confidence: 99%