The surface defects of investment castings seriously reduce the reliability of castings in service. In engineering, the surface defects of castings are usually detected by fluorescent penetrant inspection (FPI). However, due to the complexity of the image, the uneven level of inspectors and the visual fatigue caused by long-term inspection, the accuracy and efficiency of FPI are reduced. Therefore, fluorescent penetrant automatic inspection systems have been gradually developed. This paper systematically summarizes the research status of fluorescence penetrant automated inspection at home and abroad. This paper also gives the main steps of the automatic fluorescent defect detection system based on the traditional image processing method, and reports a new automatic fluorescent defect detection module based on the deep learning method. Furthermore, this paper predicts the development trend of intelligent fluorescent defect detection in investment castings.