In this paper, a new interframe difference algorithm for moving target detection is proposed which is under a static background based on three-frame-difference method in combination with background subtraction method. Firstly, the current frame image subtracts the previous frame and the next frame image separately, their results are added together to get a gray-scale image of the three-frame-difference method. Secondly, the current frame image subtracts the background image to get another gray-scale image of background subtraction method. Thirdly, their sum of the two gray-scale images of above is translated into binary image after being judged by threshold. Finally, this binary image is processed by morphology filtering and connectivity analyzing. Therefore, moving region is obtained. This new algorithm takes advantage of the good performances of three-frame-difference method and background subtraction method adequately. The analysis in theory and experiment results all show that the algorithm is better in efficiency and effect for moving target detection compared to the other similarity method.
[1]
He Ming-yi.
Integrated Feature and Its Application to Image Detection and Matching
,
2007
.
[2]
N. Otsu.
A threshold selection method from gray level histograms
,
1979
.
[3]
Jong Bae Kim,et al.
Efficient region-based motion segmentation for a video monitoring system
,
2003,
Pattern Recognit. Lett..
[4]
Min-Jea Tahk,et al.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
,
2022,
IEEE Aerospace and Electronic Systems Magazine.
[5]
V. Markandey,et al.
Motion estimation for moving target detection
,
1996,
IEEE Transactions on Aerospace and Electronic Systems.
[6]
Weng Muyun,et al.
Image Feature Detection and Matching Based on SUSAN Method
,
2006,
First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06).