Recent review on image clustering Article Swipe
In this review, image clustering problem is discussed starting from global learning based clustering approaches such as Kmeans to the recent challenges in this domain. In global learning based clustering models, cluster evaluation criteria was formulated on whole image datasets. In local learing based clustering models, local neighbourhood information in image data matrices were utilised. However, performances of local learning based clustering models may face limitations for image datasets that contain images with pose, illumination, or occlusion variations. Further, both global learning and local learning approaches were combined in clustering models. Still, image clustering performances are not significantly improved. I elaborate challenges in image clustering problem by categorising image datasets as Gaussian‐like or multimodal. Clustering performances on 14 benchmark image datasets of almost all state‐of‐the‐art clustering models are optimal only for Gaussian‐like image datasets. Thus, image clustering performance has direct correlation with the distribution of image datasets. Further, by employing optimal image descriptor, clustering performances are data dependent. Almost all exiting clustering models are based on second‐order statistics. Owing to which, multimode image patterns may not be effectively handled even by exploiting both local and global information in image data matrices.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/iet-ipr.2014.0885
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0885
- OA Status
- bronze
- Cited By
- 23
- References
- 65
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1108280307
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- OpenAlex ID
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https://openalex.org/W1108280307Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/iet-ipr.2014.0885Digital Object Identifier
- Title
-
Recent review on image clusteringWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-08-07Full publication date if available
- Authors
-
N. AhmedList of authors in order
- Landing page
-
https://doi.org/10.1049/iet-ipr.2014.0885Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0885Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0885Direct OA link when available
- Concepts
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Cluster analysis, Computer science, Artificial intelligence, Image (mathematics), Computer vision, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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23Total citation count in OpenAlex
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2025: 1, 2024: 4, 2023: 2, 2022: 2, 2021: 3Per-year citation counts (last 5 years)
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65Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |