The accurate reconstruction of industrial component edges is essential and crucial for visual positioning and quality inspection. To address the issue of difficulty in accurately reconstructing point clouds at the edges of industrial components, a three-dimensional reconstruction algorithm based on point cloud projection is proposed. First, the three-dimensional point cloud of the components is obtained by scanning using a binocular structured light method, edge points in the scanned point cloud are extracted. Then the image edge points are extracted from the binocular images. Subsequently, the point cloud edge points are projected onto the binocular images, the nearest image edge points are searched around each projected point to obtain corresponding binocular edge points. Finally, accurate three-dimensional edge point clouds are reconstructed using stereo vision methods. Experimental results demonstrate that compared to other current methods, this approach can effectively address the issue of false edges caused by interference such as reflection and surface scratches, the reconstructed edge point cloud using this method has high accuracy with reconstruction error less than 0.15 mm and can be applied in industrial scenarios such as bin picking, online quality inspection.