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.
