Large scale laser images refer to a large amount of laser scanning image data with rich information. The application of such images in fields such as geographic information acquisition, urban planning, and autonomous driving is becoming increasingly widespread, usually containing rich spatial information and detailed features. Therefore, there is a problem of high processing complexity. Cloud computing, as an emerging computing mode, has strong computing power and flexible resource allocation advantages. Research on cloud computing based rapid recognition methods for multi type large-scale laser images. Process laser images through nonlinear matching to determine the pose change matrix of target points in the laser image; Filter the processed laser images using machine algorithms to identify key features in different types of laser images; By using cloud computing correlation methods, a fast recognition model is constructed to achieve rapid recognition of multiple types of large-scale laser images through the objective function within the model. The experimental results show that using two sets of different types of continuous frame laser images as test samples, the studied method can achieve rapid recognition under the design scheme and has practical value.