TY - JOUR
T1 - ALI-TM
T2 - A moving objects detection algorithm for infrared images with dynamic background
AU - Zhao, Yufei
AU - Song, Yong
AU - Zhao, Shangnan
AU - Li, Yun
AU - Li, Xu
AU - Hao, Qun
AU - Guo, Zhengkun
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/9
Y1 - 2018/9
N2 - Moving objects detection is an important precursor of stable tracking and recognition, especially for the infrared scenes with dynamic background. In this paper, we proposed an Algorithmic Lateral Inhibition-Template Matching (ALI-TM) algorithm. This algorithm simulates the Lateral Inhibition (LI) mechanism, and achieves a good detection ability in the infrared scenes with dynamic background. First, the input infrared images are segmented into several binary images using an adaptive threshold segmentation. Then, for each binary image, the moving part can be detected by Algorithmic Lateral Inhibition (ALI) method, and the moving part includes moving objects and dynamic background. Finally, the moving objects can be separated from the dynamic background with a modified Template Matching method. Experimental validation of the ALI-TM algorithm is demonstrated on a diverse set of infrared images with dynamic background, the results showed that the proposed ALI-TM algorithm has higher detection precision, higher recognition rate, and better detection ability. Therefore the ALI-TM algorithm is capable to cope with the infrared scenes with dynamic background.
AB - Moving objects detection is an important precursor of stable tracking and recognition, especially for the infrared scenes with dynamic background. In this paper, we proposed an Algorithmic Lateral Inhibition-Template Matching (ALI-TM) algorithm. This algorithm simulates the Lateral Inhibition (LI) mechanism, and achieves a good detection ability in the infrared scenes with dynamic background. First, the input infrared images are segmented into several binary images using an adaptive threshold segmentation. Then, for each binary image, the moving part can be detected by Algorithmic Lateral Inhibition (ALI) method, and the moving part includes moving objects and dynamic background. Finally, the moving objects can be separated from the dynamic background with a modified Template Matching method. Experimental validation of the ALI-TM algorithm is demonstrated on a diverse set of infrared images with dynamic background, the results showed that the proposed ALI-TM algorithm has higher detection precision, higher recognition rate, and better detection ability. Therefore the ALI-TM algorithm is capable to cope with the infrared scenes with dynamic background.
KW - Adaptive threshold segmentation
KW - Dynamic background
KW - Infrared images
KW - Lateral Inhibition
KW - Moving objects detection
UR - http://www.scopus.com/inward/record.url?scp=85051107455&partnerID=8YFLogxK
U2 - 10.1016/j.infrared.2018.08.003
DO - 10.1016/j.infrared.2018.08.003
M3 - Article
AN - SCOPUS:85051107455
SN - 1350-4495
VL - 93
SP - 205
EP - 212
JO - Infrared Physics and Technology
JF - Infrared Physics and Technology
ER -