Camera　calibration　is　an　essential　process　in　visual　measurement.　1D　target　based　camera　calibration　can　great　facilitate　the　operating　procedure　especially　when　multiple　vision　sensors　should　be　calibrated.　However,　the　current　one-dimensional　calibration　algorithm　is　still　imprecision　in　practice.　In　this　work,　the　PSO　algorithm　is　employed　to　improve　the　precision　of　one-dimensional　camera　calibration.　Since　the　swarm　intelligence　algorithm　is　initial　value　sensitive,　in　this　work,　a　data　cluster　algorithm　is　proposed　to　get　a　better　initial　value.　To　overcome　the　over　optimizing　problem　accounted　in　swarm　intelligence　algorithm,　prior　knowledge,　such　as　the　picture’s　size,　is　employed　to　make　sure　the　parameters　will　converge　toward　the　true　values.　©　Springer　Nature　Switzerland　AG　2018.