Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Particularly in recent years, there has been increased interest in determining the ideal thresholding for picture segmentation. The best thresholding values are found using various techniques, including Otsu and Kapur-based techniques. These techniques work well for bi-level thresholding, but when u...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://depot.sorbonne.ae/handle/20.500.12458/1436 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1857415064427954177 |
|---|---|
| author | Abu Zitar, Raed |
| author2 | Otair, Mohammad Abualigah, Laith Tawfiq, Saif Alshinwan, Mohammad Ezugwu, Absalom E. Sumari, Putra |
| author2_role | author author author author author author |
| author_facet | Abu Zitar, Raed Otair, Mohammad Abualigah, Laith Tawfiq, Saif Alshinwan, Mohammad Ezugwu, Absalom E. Sumari, Putra |
| author_role | author |
| dc.creator.none.fl_str_mv | Abu Zitar, Raed Otair, Mohammad Abualigah, Laith Tawfiq, Saif Alshinwan, Mohammad Ezugwu, Absalom E. Sumari, Putra |
| dc.date.none.fl_str_mv | 2023-10-12T11:31:06Z 2023-10-12T11:31:06Z 2023 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 1380-7501 1573-7721 https://depot.sorbonne.ae/handle/20.500.12458/1436 10.1007/s11042-023-17221-9 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Multimedia Tools and Applications |
| dc.subject.none.fl_str_mv | Image segmentation Multi-level thresholding Meta-heuristic algorithms Arithmetic optimization algorithm |
| dc.title.none.fl_str_mv | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | Particularly in recent years, there has been increased interest in determining the ideal thresholding for picture segmentation. The best thresholding values are found using various techniques, including Otsu and Kapur-based techniques. These techniques work well for bi-level thresholding, but when used to find the appropriate thresholds for multi-level thresholding, there will be issues with long calculation times, high computational costs, and the need for accuracy improvements. This work investigates the capability of the Arithmetic Optimization Algorithm to discover the best multilayer thresholding for picture segmentation to circumvent this issue. The leading mathematical arithmetic operators' distributional nature is used by the AOA method. The picture histogram was used to construct the candidate solutions in the modified algorithms, which were then updated according to the algorithm's features. The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. The proposed approach is tested on five frequent photos from the Berkeley University database. The fitness function, root-mean-squared error, peak signal-to-noise ratio, and other widely used assessment metrics were utilized to assess the performance of the suggested segmentation approach. Many benchmark pictures were employed to verify the suggested technique's effectiveness and evaluate it against other well-known optimization methods described in the literature. |
| id | sorbonner_f3f0c4d30c094592b0f4e4905a52cf0f |
| identifier_str_mv | 1380-7501 1573-7721 10.1007/s11042-023-17221-9 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1436 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray imagesAbu Zitar, RaedOtair, MohammadAbualigah, LaithTawfiq, SaifAlshinwan, MohammadEzugwu, Absalom E.Sumari, PutraImage segmentationMulti-level thresholdingMeta-heuristic algorithmsArithmetic optimization algorithmParticularly in recent years, there has been increased interest in determining the ideal thresholding for picture segmentation. The best thresholding values are found using various techniques, including Otsu and Kapur-based techniques. These techniques work well for bi-level thresholding, but when used to find the appropriate thresholds for multi-level thresholding, there will be issues with long calculation times, high computational costs, and the need for accuracy improvements. This work investigates the capability of the Arithmetic Optimization Algorithm to discover the best multilayer thresholding for picture segmentation to circumvent this issue. The leading mathematical arithmetic operators' distributional nature is used by the AOA method. The picture histogram was used to construct the candidate solutions in the modified algorithms, which were then updated according to the algorithm's features. The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. The proposed approach is tested on five frequent photos from the Berkeley University database. The fitness function, root-mean-squared error, peak signal-to-noise ratio, and other widely used assessment metrics were utilized to assess the performance of the suggested segmentation approach. Many benchmark pictures were employed to verify the suggested technique's effectiveness and evaluate it against other well-known optimization methods described in the literature.2023-10-12T11:31:06Z2023-10-12T11:31:06Z2023Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal articleapplication/pdf1380-75011573-7721https://depot.sorbonne.ae/handle/20.500.12458/143610.1007/s11042-023-17221-9enMultimedia Tools and Applicationsoai:depot.sorbonne.ae:20.500.12458/14362024-07-17T18:00:34Z |
| spellingShingle | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images Abu Zitar, Raed Image segmentation Multi-level thresholding Meta-heuristic algorithms Arithmetic optimization algorithm |
| title | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| title_full | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| title_fullStr | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| title_full_unstemmed | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| title_short | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| title_sort | Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images |
| topic | Image segmentation Multi-level thresholding Meta-heuristic algorithms Arithmetic optimization algorithm |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1436 |