Three-cube-based fluorescence resonance energy transfer (E-FRET) microscopy is the most popular live-cell quantitative FRET imaging technique owing to its high sensitivity, no damage and fast measurement speed. To realize live-cell online real-time quantitative FRET imaging, we propose an automatic cell imaging background recognition and threshold setting method that counts gray values of an image pixel by pixel and assign the first peak gray value in the corresponding gray value-count plot as the background. The β (the empirical constant) times of the background value are set as a threshold. The corrected donor-excitation and donor-detection, and acceptor-excitation and acceptor-detection images obtained by subtracting the corresponding threshold from the raw images are used to create a Boolean logic template for data filtering of the FRET efficiency and relative concentration ratio between the acceptor and the donor via logical and operation. The results obtained through online dynamic quantitative E-FRET images of live cells expressing different plasmids on our self-assembled automatic E-FRET microscope are consistent with the expected values.