Evaluation of Moving Object Detection Methods based on General Purpose Single Board Computer

Agung Nugroho Jati, Ledya Novamizanti, Mirsa Bayu Prasetyo, Andy Ruhendy Putra


RGA and SKDA are two different methods which can be used to detect the object in image based processing. In order to support the moving surveillance camera system which proposed in Telkom University, RGA and SKDA have tested to be reviewed which more reliable to be implemented in a single board computer. In this paper, will be discussed about implementation and testing of two different methods of object detection using backgrounds subtraction. For implementation, each of them will be combined with Extended Kalman Filter in a Raspberry Pi. The parameter which have tested are memory and CPU usage, and system utilization.   The result shows that RGA is more reliable than SKDA to implemented in SBC because of less CPU usage and system utilization.


DOI: http://dx.doi.org/10.11591/telkomnika.v14i1.7257


Running Gaussian Average (RGA); Sequential Kernel Density Approximation (SKDA); Extended Kalman Filter; Single Board Computer (SBC); Raspberry Pi

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