Background: High Content Image (HCI), an automatic imaging and analysis system, provides a fast drug screening method by detecting the subcellular distribution of protein in intact cells. Objective: This study established the first standardized HCI platform for lipopolysaccharide (LPS)-induced RAW264.7 macrophages to screen anti-inflammatory compounds by measuring nuclear factor-κB (NF-κB) nuclear translocation. Methods: The influence of the cell passages, cell density, LPS induction time and concentration, antibody dilution, serum, dimethyl sulfoxide, and analysis parameters on NF-κB nuclear translocation and HCI data quality was optimized. The BAY-11-7085, the positive control for inhibiting NF-κB, and the Western blot assay were separately employed to verify the stability and reliability of the platform. Lastly, the effect of BHA on NO release, iNOS expression, IL-1β, IL-6, and TNF-α mRNA in LPS-induced RAW264.7 cells was detected. Results: The optimal conditions for measuring NF-κB translocation in LPS-induced RAW264.7 cells by HCI were established. Cells that do not exceed 22 passages were seeded at a density of 10 k cells/well and pretreated with compounds following 200 ng/mL LPS for 40 min. Parameters including the nuclear area of 65 µm, cell area of 80 µm, collar of 0.9 µm, and sensitivity of 25% were recommended for image segmentation algorithms in the analysis workstation. Benzoylhypaconine from aconite was screened for the first time as an anti-inflammatory candidate by the established HCI platform. The inhibitory effect of benzoylhypaconine on NF-κB translocation was verified by Western blot. Furthermore, benzoylhypaconine reduced the release of NO, inhibited the expression of iNOS, and decreased the mRNA levels of IL-1β, IL-6, and TNF-α. Conclusion: The established HCI platform could be applied to screen anti-inflammatory compounds by measuring the NF-κB nuclear translocation in LPS-induced RAW264.7 cells.