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Cuttlefish Algorithm-Based Multilevel 3-D Otsu Function for Color Image Segmentation.
- Source :
-
IEEE Transactions on Instrumentation & Measurement . May2020, Vol. 69 Issue 5, p1871-1880. 10p. - Publication Year :
- 2020
-
Abstract
- To overcome the shortcomings of 1-D and 2-D Otsu’s thresholding methods, a 3-D Otsu method has been introduced. While yielding satisfactory segmentation results for images with a low signal-to-noise ratio (SNR) and poor contrast, it has the downside of high computational complexity. In this paper, the cuttlefish algorithm (CFA)-based 3-D Otsu thresholding method is proposed to pace up the conventional 3-D Otsu thresholding for color image segmentation. In order to decrease the effects of noises and weak edges, an optimally selected multilevel 3-D Otsu image thresholding technique is brought into the proposed segmentation scheme. The CFA is a newly developed stochastic meta-heuristic optimization algorithm based on observing, mimicking, and modeling the camouflaging feature of cuttlefish. It is used to simplify the problem of exhaustive search for the optimal threshold vector in 3-D space. Experimental results, when compared to 1-D Otsu, 1-D Otsu-Cuckoo search (CS) algorithm, 1-D Otsu-lightning search algorithm (LSA), 1-D Otsu-CFA, conventional 3-D Otsu, 3-D Otsu-CS, and 3-D Otsu-LSA, indicate that the proposed algorithm CFA-based 3-D Otsu thresholding is superior to all the other multilevel thresholding algorithms. The proposed 3-D-CFA method produces promising segmentation results from the objective and subjective aspects. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189456
- Volume :
- 69
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Instrumentation & Measurement
- Publication Type :
- Academic Journal
- Accession number :
- 143313621
- Full Text :
- https://doi.org/10.1109/TIM.2019.2922516