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http://dx.doi.org/10.6109/jkiice.2015.19.10.2380

A Hardware Implementation of EGML-based Moving Object Detection Algorithm  

Kim, Gyeong-hun (School of Electronic Engineering, Kumoh National Institute of Technology)
An, Hyo-sik (School of Electronic Engineering, Kumoh National Institute of Technology)
Shin, Kyung-wook (School of Electronic Engineering, Kumoh National Institute of Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.10, 2015 , pp. 2380-2388 More about this Journal
Abstract
A hardware implementation of MOD(moving object detection) algorithm using EGML(effective Gaussian mixture learning)- based background subtraction to detect moving objects in video is described. Some approximations of EGML calculations are applied to reduce hardware complexity, and pipelining technique is adopted to improve operating speed. The MOD processor designed in Verilog-HDL has been verified by FPGA-in-the-loop verification using MATLAB/Simulink. The MOD processor has 2,218 slices on the Virtex5-XC5VSX95T FPGA device and its throughput is 102 MSamples/s at 102 MHz clock frequency. Evaluation results of the MOD processor for 12 images in the IEEE CDW-2012 dataset show that the average recall value is 0.7631, the average precision value is 0.7778 and the average F-measure value is 0.7535.
Keywords
moving object detection; MOD; background subtraction; gaussian mixture model; EGML;
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