Integrating agent-based models and clustering methods for improving image segmentation Article Swipe
Erik Cuevas
,
Sonia García-De-Lira
,
Cesar Ascencio-Piña
,
Marco Pérez‐Cisneros
,
S. Castaneda Vega
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.heliyon.2024.e40698
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.heliyon.2024.e40698
Image segmentation through clustering is a widely used technique in computer vision that partitions an image into multiple segments by grouping pixels based on feature similarity. Although effective for certain applications, this approach often struggles with the complexity of real-world images, where noise and random variations can significantly affect feature homogeneity, leading to incorrect pixel classifications. To address these limitations, this paper introduces a novel hybrid image segmentation method that combines an agent-based model with a clustering technique to enhance segmentation accuracy and robustness. The method starts with an agent-based model as a preprocessing step aimed at homogenizing pixel intensities within each region. In this model, pixels adjust their intensities based on a consensus reached within their neighborhood, promoting a more uniform feature distribution. Subsequently, the Firefly metaheuristic clustering method is applied to segment the preprocessed image into distinct regions. Metaheuristic techniques, distinguished from classical clustering methods, possess the capability to adaptively navigate through a broad solution space to discover optimal clustering configurations. This adaptability makes them suitable for complex image datasets. The efficacy of the proposed hybrid segmentation method has been tested on various images, employing key quality indices for evaluation. Experimental outcomes demonstrate that this approach yields superior segmented images, showcasing enhanced quality and robustness compared to other segmentation methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.heliyon.2024.e40698
- OA Status
- gold
- Cited By
- 3
- References
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4404871629Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.heliyon.2024.e40698Digital Object Identifier
- Title
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Integrating agent-based models and clustering methods for improving image segmentationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-29Full publication date if available
- Authors
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Erik Cuevas, Sonia García-De-Lira, Cesar Ascencio-Piña, Marco Pérez‐Cisneros, S. Castaneda VegaList of authors in order
- Landing page
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https://doi.org/10.1016/j.heliyon.2024.e40698Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.heliyon.2024.e40698Direct OA link when available
- Concepts
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Cluster analysis, Computer science, Image segmentation, Artificial intelligence, Segmentation, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
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58Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W6624003150, https://openalex.org/W6696428399, https://openalex.org/W6735924745, https://openalex.org/W6849089231, https://openalex.org/W4388295245, https://openalex.org/W2800561367, https://openalex.org/W6687171081, https://openalex.org/W6861287854, https://openalex.org/W6767034923, https://openalex.org/W6684905197, https://openalex.org/W6797858007, https://openalex.org/W2032227103, https://openalex.org/W2006982476, https://openalex.org/W6996185213, https://openalex.org/W2000063966, https://openalex.org/W4393389000, https://openalex.org/W6846934049, https://openalex.org/W4362702150, https://openalex.org/W4322738381, https://openalex.org/W4360981108, https://openalex.org/W6641595364, https://openalex.org/W4372232603, https://openalex.org/W4311461418, https://openalex.org/W6631478494, https://openalex.org/W2044587647, https://openalex.org/W6862388052, https://openalex.org/W6720719261, https://openalex.org/W6774312386, https://openalex.org/W6649660197, https://openalex.org/W2125319195, https://openalex.org/W6677825111, https://openalex.org/W2602799623, https://openalex.org/W6630983829, https://openalex.org/W6941289403, https://openalex.org/W2972155310, https://openalex.org/W1977556410, https://openalex.org/W6683280141, https://openalex.org/W3104313545, https://openalex.org/W4310506223, https://openalex.org/W4235416656, https://openalex.org/W2252646842, https://openalex.org/W1804610594, https://openalex.org/W4392203599, https://openalex.org/W2289076519, https://openalex.org/W4238686949, https://openalex.org/W2188292956, https://openalex.org/W2620971809, https://openalex.org/W4294268831, https://openalex.org/W4313555467, https://openalex.org/W4254732145, https://openalex.org/W2990714382, https://openalex.org/W267983876, https://openalex.org/W2152513128, https://openalex.org/W1265389026, https://openalex.org/W4392785972, https://openalex.org/W2904730701, https://openalex.org/W2473745301, https://openalex.org/W4229799326 |
| referenced_works_count | 58 |
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