Image Segmentation by Agent-Based Pixel Homogenization
Image segmentation is the process of partitioning an image into multiple regions or objects, each representing a coherent and meaningful part of the image. Segmentation methods are highly sensitive to the lack of homogeneity in regions or objects owing to noise and intensity inconsistencies. Under s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10124930/ |
| _version_ | 1797808471619403776 |
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| author | Ernesto Ayala Erik Cuevas Daniel Zaldivar Marco Perez |
| author_facet | Ernesto Ayala Erik Cuevas Daniel Zaldivar Marco Perez |
| author_sort | Ernesto Ayala |
| collection | DOAJ |
| description | Image segmentation is the process of partitioning an image into multiple regions or objects, each representing a coherent and meaningful part of the image. Segmentation methods are highly sensitive to the lack of homogeneity in regions or objects owing to noise and intensity inconsistencies. Under such conditions, most approaches exhibit poor quality performance. This paper proposes an agent-based model approach for homogenization of images to reduce the presence of noisy pixels and undesirable artifacts. In our approach, each pixel in the image represents an agent, and a set of rules evaluates the states of neighboring agents to modify the intensity values of each pixel iteratively until different regions from the image assume homogeneous grayscale levels. The proposed method has been used in combination with the Otsu’s method to evaluate its performance in image segmentation. The approach was evaluated with different types of images considering their homogeneity. Experimental results indicated that the proposed approach produces better-segmented images in terms of quality and robustness. |
| first_indexed | 2024-03-13T06:38:00Z |
| format | Article |
| id | doaj.art-5360d847f35e4519a5b5064359680163 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T06:38:00Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5360d847f35e4519a5b50643596801632023-06-08T23:00:51ZengIEEEIEEE Access2169-35362023-01-0111542215423910.1109/ACCESS.2023.327672110124930Image Segmentation by Agent-Based Pixel HomogenizationErnesto Ayala0https://orcid.org/0009-0005-1007-5393Erik Cuevas1https://orcid.org/0000-0002-0358-6049Daniel Zaldivar2Marco Perez3Departamento de Electrónica y Computación, CUCEI, University of Guadalajara, Jalisco, Guadalajara, MexicoDepartamento de Electrónica y Computación, CUCEI, University of Guadalajara, Jalisco, Guadalajara, MexicoDepartamento de Electrónica y Computación, CUCEI, University of Guadalajara, Jalisco, Guadalajara, MexicoDepartamento de Electrónica y Computación, CUCEI, University of Guadalajara, Jalisco, Guadalajara, MexicoImage segmentation is the process of partitioning an image into multiple regions or objects, each representing a coherent and meaningful part of the image. Segmentation methods are highly sensitive to the lack of homogeneity in regions or objects owing to noise and intensity inconsistencies. Under such conditions, most approaches exhibit poor quality performance. This paper proposes an agent-based model approach for homogenization of images to reduce the presence of noisy pixels and undesirable artifacts. In our approach, each pixel in the image represents an agent, and a set of rules evaluates the states of neighboring agents to modify the intensity values of each pixel iteratively until different regions from the image assume homogeneous grayscale levels. The proposed method has been used in combination with the Otsu’s method to evaluate its performance in image segmentation. The approach was evaluated with different types of images considering their homogeneity. Experimental results indicated that the proposed approach produces better-segmented images in terms of quality and robustness.https://ieeexplore.ieee.org/document/10124930/Agent-based modelbinarizationpixel homogenizationsegmentation |
| spellingShingle | Ernesto Ayala Erik Cuevas Daniel Zaldivar Marco Perez Image Segmentation by Agent-Based Pixel Homogenization IEEE Access Agent-based model binarization pixel homogenization segmentation |
| title | Image Segmentation by Agent-Based Pixel Homogenization |
| title_full | Image Segmentation by Agent-Based Pixel Homogenization |
| title_fullStr | Image Segmentation by Agent-Based Pixel Homogenization |
| title_full_unstemmed | Image Segmentation by Agent-Based Pixel Homogenization |
| title_short | Image Segmentation by Agent-Based Pixel Homogenization |
| title_sort | image segmentation by agent based pixel homogenization |
| topic | Agent-based model binarization pixel homogenization segmentation |
| url | https://ieeexplore.ieee.org/document/10124930/ |
| work_keys_str_mv | AT ernestoayala imagesegmentationbyagentbasedpixelhomogenization AT erikcuevas imagesegmentationbyagentbasedpixelhomogenization AT danielzaldivar imagesegmentationbyagentbasedpixelhomogenization AT marcoperez imagesegmentationbyagentbasedpixelhomogenization |