Aiming at the problem of bridge disease detection, especially the crack detection with high degree of damage, combined with the previous bridge detection system, an improved bridge detection system was proposed in this study. The hardware of the improved system is the DJI M210-RTK Unmanned Aerial Vehicle (UAV), and the software consists of image data acquisition module, crack detection module, and a module of 3D model building. In this study, calculation function of crack length and width is added to the crack detection module, and the length of the crack is calculated by curve fitting after iteration, besides, skeleton method is used to calculate the width. In the experiment, by setting the flight path, scanning distance, shooting distance of the UAV and the sub-region number of the bridge pier to be tested in advance, 200 pictures of the bridge pier deck and the video data of the bridge were collected. By identifying the crack types of bridge deck, and calculating length and width of crack, it can make us having a more comprehensive understanding of crack information and the degree of damage, and manual measurement in later period can be reduced, besides, combined with Ubuntu 16.04 system, the 3D model can easily and intuitively display the general situation of the bridge with using Direct Sparse Odometry (DSO) to carry out bridge 3D modeling. The improved system is stable, the method saves time and effort, and has wide applicability, especially for the detection of some sea-crossing bridges and bridges with complex surrounding environments.