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Proceedings Paper

Application of cuckoo search algorithm for texture recognition based on water areas
Author(s): Kangbo Peng; Zhongwei Chen; Lai Huang; Xiaozhong Wu
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Paper Abstract

Texture recognition is a key topic in many applications of image analysis; many techniques have been proposed to measure the characteristics of this field. Among them, texture energy extracted with the “Tuned” mask is a rotation and scale invariant texture descriptor. However, the tuning process is computationally intensive and easily to trap into local optimum. In the proposed approach, how to obtain the “Tuned” mask is viewed as a combinatorial optimization problem and the optimal 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 recognition, the recognition accuracy is higher than genetic algorithm (GA) and particle swarm optimization (PSO) optimized “Tuned” mask scheme, and the water areas can be well recognized from the original image. It is a robust and efficient method to obtain the optimal “Tuned” mask for texture analysis.

Paper Details

Date Published: 9 August 2018
PDF: 6 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080620 (9 August 2018); doi: 10.1117/12.2503078
Show Author Affiliations
Kangbo Peng, State Grid Hunan Electric Power Corporation Economy Institute (China)
Zhongwei Chen, State Grid Hunan Electric Power Corporation Economy Institute (China)
Lai Huang, State Grid Hunan Electric Power Co., Ltd. (China)
Xiaozhong Wu, State Grid Hunan Electric Power Co., Ltd. (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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