To realize online detection of solder ball quality and coplanarity in Ball Grid Array chip visual inspection, a detection method combining point cloud and image data is proposed. First, the color camera has been calibrated, the chips color image and point cloud data were acquired, and the unit normal vector of the main plane in the workpiece is achieved by Random sample consensus. The point cloud is rotated to fulfill the tilt of the point cloud alignment. Then, the rotating point cloud is projected and imaged by the color camera’s internal and external parameters, to produce the point cloud grayscale image, which is matched with the color image in point mode, and the translation amount and deflection angle between the point cloud data and the color image are obtained to complete the point cloud. In this way, the point cloud data is registered with the color image data. The solder ball is extracted from the registered data to determine its size, breakage, deformation, bridge, and other faults, as well as to measure its height and complete the solder ball’s coplanarity measurement. To perform comparison trials, this method was compared with the ICP algorithm. Two measurement results show that the proposed method can save 62.8% of the time, which also has consistent detection results. The proposed method for 3D point cloud has a wide application prospect in advanced manufacturing.