Image Segmentation Using Multilevel Thresholding: A Research Review

Image segmentation is a basic problem in computer vision and various image processing applications. Over the years, commonly used image segmentation has become quite challenging because of its utilization in many applications. Image thresholding is one of the most exploited techniques to accomplish...

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Veröffentlicht in:Iranian journal of science and technology. Transactions of electrical engineering Jg. 44; H. 1; S. 1 - 29
Hauptverfasser: Pare, S., Kumar, A., Singh, G. K., Bajaj, V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.03.2020
Schlagworte:
Electrical Engineering
Engineering
Review Paper
Kapur’s entropy
Tsalli’s entropy
Image segmentation
Multilevel thresholding
Nature-inspired optimization algorithms
Between-class variance
ISSN:2228-6179, 2364-1827
Online-Zugang:Volltext
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Zusammenfassung:Image segmentation is a basic problem in computer vision and various image processing applications. Over the years, commonly used image segmentation has become quite challenging because of its utilization in many applications. Image thresholding is one of the most exploited techniques to accomplish image segmentation. Multilevel thresholding is found to be most appropriate and well known among all the image segmentation techniques. The segmented image quality is based on the techniques incorporated to choose the threshold value. In this paper, an exhaustive survey has been carried out, considering both the general purpose and satellite images to cover the performance comparison of various image segmentation approaches based on meta-heuristics optimization algorithms, present in the literature for multilevel image thresholding. In addition, this paper also focuses on information theoretic approach-based objective criterion using different statistical properties such as between-class variance, entropy, moment and maximum likelihood for selecting multilevel thresholds. A list of 157 publications on the subject is also appended for quick reference.
ISSN:2228-6179
2364-1827
DOI:10.1007/s40998-019-00251-1