A Fast Decomposed Three-dimensional OTSU Algorithm Based on Cuckoo Search for Image Segmentation

Xiao Yang; Lie-Jun Wang; Ji-Wei  Qin; Hang Zuo

doi:10.6180/jase.201809_21(3).0016

A Fast Decomposed Three-dimensional OTSU Algorithm Based on Cuckoo Search for Image Segmentation

Computer Science and Information Engineering

Xiao Yang¹, Lie-Jun Wang This email address is being protected from spambots. You need JavaScript enabled to view it.², Ji-Wei Qin³ and Hang Zuo¹

¹College of Information Science and Engineering, Xinjiang University, Urumqi Xinjiang 830046, P.R. China
²College of Software, Xinjiang University, Urumqi Xinjiang 830046, P.R. China
³Network and Information Technology Center, Xinjiang University, Urumqi Xinjiang 830046, P.R. China

Received: August 11, 2017
Accepted: April 9, 2018
Publication Date: September 1, 2018

Download Citation: ||https://doi.org/10.6180/jase.201809_21(3).0016

ABSTRACT

Image threshold method is an important technique for image segmentation. The maximum between-class variance of pixel (Otsu) algorithm has been widely applied in the literature. However, the original Otsu method for image segmentation is very time-consuming,and the segmentation results are often unstable for the image with low signal to noise ratio (SNR). In this paper, a fast image segmentation method (D3OTSU-CS), decomposed three-dimensional Otsu based on the technology of the cuckoo search (CS), is proposed. The proposed method starts by overcoming the complex computational by decomposing the original three-dimensional Otsu into a one-dimensional Otsu and a two-dimensional Otsu. The cuckoo search algorithm is employed to find the optimal threshold vector by the global Lévy flight searching, and the between-class variance of the two-dimensional Otsu is investigated as fitness functions. The Experimental results are illustrated to show that the computation time efficiency of the proposed method is increased by about 98.6% than the 3OTSU. In addition, the stability and reliability of the segmentation results by the proposed method outperform 2OTSU and 3OTSU.

Keywords: Image Segmentation, Otsu Algorithm, Cuckoo Search, Lévy Flight, Nature-inspired Strategy

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