Printing registration algorithm based on statistical outlier removal and sparsity optimization
SHU Jun1,2， DENG Mingzhou1,2， LEI Jianjun3， YANG Li3
(1.School of Electrical and Electronic Engineering， Hubei University of Technology， Wuhan 430068， China；2.Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System，Hubei University of Technology， Wuhan 430068， China；3. College of Computer， Hubei University of Education， Wuhan 430068，China)
Abstract：In digital printing technology， the traditional global printing pattern registration method cannot meet the requirements in terms of accuracy and efficiency. The local printing pattern registration method has the problem of large registration errors resulting in large matching errors， and low algorithm efficiency coused by too many image distortion control points. This paper proposes a new registration method for partial printing patterns is proposed. This method is based on statistical outlier removal registration optimization algorithm to reduce the error points in the FLANN matching points. Based on analyzing the characteristics of redundant control points in image deformation， a redundancy optimization algorithm based on sparsity is proposed to reduce the number of control points. Experimental results show that this method can effectively filter out the error points after registration， optimize the set of control points， and improve the overall registration accuracy and algorithm efficiency.
2021, Vol. 55 
