Lionel L. Sop Deffo

Work place: University of Dschang, Cameroon



Research Interests: Image Processing, Neural Networks, Computer Vision, Computational Learning Theory, Computer systems and computational processes


Lionel L. Landry SOP DEFFO, male, is a Master of Science holder in computer science option network and distributed services where he has worked on a multi criterion approach for energy minimization and quality of service in a mobile ahdoc network (MANET). He is currently a PhD student at the University of Dschang Cameroon. His research interest includes image processing, computer vision, machine learning and more specifically neural network and deep leaning

Author Articles
EFF-ViBE: An Efficient and Improved Background Subtraction Approach based on ViBE

By Elie Tagne Fute Lionel L. Sop Deffo Emmanuel TONYE

DOI:, Pub. Date: 8 Feb. 2019

Background subtraction plays an important role in intelligent video surveillance since it is one of the most used tools in motion detection. If scientific progress has enabled to develop sophisticated equipment for this task, algorithms used should be improved as well. For the past decade a background subtraction technique called ViBE is gaining the field. However, the original algorithm has two main drawbacks. The first one is ghost phenomenon which appears if the initial frame contains a moving object or in the case of a sudden change in the background situations. Secondly it fails to perform well in complicated background. This paper presents an efficient background subtraction approach based on ViBE to solve these two problems. It is based on an adaptive radius to deal with complex background, on cumulative mean and pixel counting mechanism to quickly eliminate the ghost phenomenon and to adapt to sudden change in the background model.

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