The Visible Infrared Imaging Radiometer (VIIRS) day/night band (DNB) onboard Suomi National Polar-orbiting Partnership (NPP) satellite offers a wide range of applications at night, ranging from fire detection, meteorological phenomena to observations of anthropogenic light sources. It is becoming a useful tool to monitor and quantify these ships by detecting the light emitted by the lamps. In this study, a threshold-based method is presented to automatically identify the ships. Before detection, several pre-processing steps including contrast enhancement and instrument noise removal are conducted; then the background value is subtracted from the original image to reduce the blurred area around the target, which can further make the gathered ships isolated; In addition, the effects of some interference sources such as ionospheric energetic particles and thin clouds are also taken into consideration for improving the detection rate. Finally, the proposed threshold-based method is applied to the DNB images over study areas in Yellow Sea and Bohai Sea in China. The detection results show that the proposed method can detect more than 81% of ships when comparing with those from Automatic Identification System (AIS).