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General Information
Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2015 Vol.7(3): 197-200 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.956

The Flocs Target Detection Algorithm Based on the Three Frame Difference and Enhanced Method of the Otsu

Xin Xie, Huiping Li, and Fengping Hu
Abstract—At present, the commonly used floc tracking algorithms are susceptible to noise, light, and floc movement speed, etc., it is difficult to extract complete moving flocs, therefore put forward a flocs target detection algorithm based on the three frame difference and particle swarm optimization & enhanced method of the Otsu. The algorithm firstly conducts difference of three consecutive frames, then use particle swarm optimization & enhanced method of the Otsu to obtain the best threshold, the optimal threshold is adopted to the image binarization and then do image post-processing, eventually obtaining a clear floc target, to lay a foundation for subsequent automation analysis of floc. Experiments show that the algorithm has the characteristics of fast, accurate, and can extract flocs target effectively.

Index Terms—Three frame difference, particle swarm optimization & enhanced method of the Otsu, optimal threshold, flocs target detection.

Xin Xie and Huiping Li are with the East China Jiaotong University of information Engineering College, Nanchang, China (e-mail: xienew@gmail.com, 812584127@qq.com).
Fengping Hu is with School of Civil Engineering, ECJT University, Nanchang, Jiangxi, China (e-mail: hufegnping1968@126.com).

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Cite:Xin Xie, Huiping Li, and Fengping Hu, "The Flocs Target Detection Algorithm Based on the Three Frame Difference and Enhanced Method of the Otsu," International Journal of Computer Theory and Engineering vol. 7, no. 3, pp. 197-200, 2015.

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