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

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.