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Mathematical Problems in Engineering
Volume 2018 (2018), Article ID 4127305, 15 pages
Research Article

A Multiframes Integration Object Detection Algorithm Based on Time-Domain and Space-Domain

College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China

Correspondence should be addressed to Zhenjiang Cai; moc.361@56jzc

Received 26 September 2017; Revised 16 January 2018; Accepted 21 January 2018; Published 20 February 2018

Academic Editor: Simone Bianco

Copyright © 2018 Yifan Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to overcome the disadvantages of the commonly used object detection algorithm, this paper proposed a multiframes integration object detection algorithm based on time-domain and space-domain (MFITS). At first, the consecutive multiframes were observed in time-domain. Then the horizontal and vertical four-direction extension neighborhood of each target pixel were selected in space-domain. Transverse and longitudinal sections were formed by fusing of the time-domain and space-domain. The mean and standard deviation of the pixels in transverse and longitudinal section were calculated. We also added an improved median filter to generate a new pixel in each target pixel position, eventually to generate a new image. This method is not only to overcome the RPAC method affected by lights, shadows, and noise, but also to reserve the object information to the maximum compared with the interframe difference method and overcome the difficulty in dealing with the high frequency noise compared with the adaptive background modeling algorithm. The experiment results showed that the proposed algorithm reserved the motion object information well and removed the background to the maximum.