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A pixel-based color image segmentation using support vector machine and fuzzy -means
Abstract
Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. In this paper, we present a pixel-based color image segmentation using Support Vector Machine (SVM) and Fuzzy C-Means (FCM). Firstly, the pixel-level color feature and texture feature of the image, which is used as input of the SVM model (classifier), are extracted via the local spatial similarity measure model and Steerable filter. Then, the SVM model (classifier) is trained by using FCM with the extracted pixel-level features. Finally, the color image is segmented with the trained SVM model (classifier). This image segmentation can not only take full advantage of the local information of the color image but also the ability of the SVM classifier. Experimental evidence shows that the proposed method has a very effective computational behavior and effectiveness, and decreases the time and increases the quality of color image segmentation in comparison with the state-of-the-art segmentation methods recently proposed in the literature.
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“Castellana et al . [168] performed the combination of both supervised and unsupervised modes of change detection and on a pixel-based method to achieve better classification of remote sensing images.”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [168]
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Research works printed but not linked: 27
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Cited by
Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68
Metadata
- Authors
- Wang, X.-Y., Zhang, X.-J., Yang, H.-Y., & Bu, J.
- Affiliations
- Liaoning Normal University (CN)
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2012-09
- Volume
- 33
- Pages
- 148-159
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2139662573
- Cited by
- 42
- References
- 0
- Citations by year
- 2024: 2 · 2023: 2 · 2022: 6 · 2021: 2 · 2020: 2 · 2019: 6 · 2018: 1 · 2017: 4 · 2016: 8 · 2015: 1 · 2014: 5 · 2013: 2 · 2012: 1
- FWCI
- 2.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neural Networks (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Remote-Sensing Image Classification
- Keywords
- color image segmentation, pixel-level segmentation, support vector machine, fuzzy c-means clustering, texture features, steerable filters, color features, pixel classification
- MeSH terms
- Color Perception, Humans, Pattern Recognition, Automated, Photic Stimulation, Fuzzy Logic, Support Vector Machine
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