Open AccessMoving object detection of assembly components based on improved background subtraction algorithm
Author(s) -
K Zhang,
Shuzhen Tong,
Hao Shi,
Guiyang Yue,
Jingxuan Zhao
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1009/1/012063
Subject(s) - computer vision , artificial intelligence , computer science , background subtraction , brightness , histogram equalization , histogram , noise (video) , basis (linear algebra) , image (mathematics) , adaptive histogram equalization , image processing , representation (politics) , algorithm , image subtraction , image texture , pixel , mathematics , binary image , physics , geometry , politics , law , political science , optics
In the automatic assembly of mechanical components, it is difficult to guarantee the quality of assembly image acquisition caused by the change of assembly environment. Firstly, the color space is compared and analysed, and histogram equalization is used to preprocess the image to reduce the impact of image brightness on subsequent processing. Then, based on the texture features of the image, an image reconstruction idea from coarse to fine is created, and an image representation method from macro to micro is established to suppress the pseudo texture and noise texture in image processing. On this basis, an adaptive threshold algorithm based on the target distance is proposed to improve the detection accuracy of the assembly target. Experimental results show that the proposed algorithm can significantly improve the detection accuracy of moving objects in assembly video frames.