Transparent materials are widely used in aerospace and optical equipment and other fields. But, due to their specular properties and optical properties, such as transmission and multiple reflections, efficient automatic detection methods for their tiny defects are difficult in the field. The main defect is the extremely low contrast of defect imaging. To obtain high-contrast images of defects, the existing methods need to adopt complex system structures or repeated angle adjustments. In this article, based on the modulation effect of defect morphology on structured light, a high-contrast defect imaging method with simple structure is proposed. The method is not sensitive to camera angle. Compared with the current dark field illumination method, the experimental results in different thickness defect specimens show that the contrast of the images collected by this method has an average of 27. 58% and a maximum of 37. 41% improvement in the impact damage, scratches, and abrasion defects. The proposed method improves the defect contrast from the perspective of imaging, and contains richer defect feature information. When using a variety of deep learning detection algorithms for comparative experiments, the current best dark-field lighting method has a maximum mAP of only 34% , while the method in this article is close to 80% , which is a significant improvement.