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A Water-Area Recognition Approach Based on “Tuned” Texture Mask and Cuckoo Search Algorithm
Joint Authors
Chen, Zhongwei
Peng, Kangbo
Huang, Lai
Wang, Yichao
Wu, Xiaozhong
Xiao, Zhenfeng
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-09
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Texture feature extraction is a key topic in many applications of image analysis; a lot of techniques have been proposed to measure the characteristics of this field.
Among them, texture energy extracted with a mask is a rotation and scale invariant texture descriptor.
However, the tuning process is computationally intensive and easily trap into the local optimum.
In the proposed approach, a “Tuned” mask is utilized to extract water and nonwater texture; the optimal “Tuned” mask is acquired by maximizing the texture energy value via a newly proposed cuckoo search (CS) algorithm.
Experimental results on samples and images show that the proposed method is suitable for texture feature extraction, the recognition accuracy is higher than the genetic algorithm (GA), particle swarm optimization (PSO) and the gravitational search algorithm (GSA) optimized “Tuned” mask scheme, and the water area could be well recognized from the original image.
Experimental results show that the proposed method could exhibit better performance than other methods involved in the paper in terms of optimization ability and recognition result.
American Psychological Association (APA)
Chen, Zhongwei& Peng, Kangbo& Huang, Lai& Wang, Yichao& Wu, Xiaozhong& Xiao, Zhenfeng. 2018. A Water-Area Recognition Approach Based on “Tuned” Texture Mask and Cuckoo Search Algorithm. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1130837
Modern Language Association (MLA)
Chen, Zhongwei…[et al.]. A Water-Area Recognition Approach Based on “Tuned” Texture Mask and Cuckoo Search Algorithm. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1130837
American Medical Association (AMA)
Chen, Zhongwei& Peng, Kangbo& Huang, Lai& Wang, Yichao& Wu, Xiaozhong& Xiao, Zhenfeng. A Water-Area Recognition Approach Based on “Tuned” Texture Mask and Cuckoo Search Algorithm. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1130837
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130837