The detection of water source microorganisms is of great significance to the biosafety of water source and so on. However, the traditional methods such as microscopic observation are inefficient and need professional personnel. Therefore, an automatic recognition method of micro-organisms in water source is proposed. Water samples were collected and a microorganisms image set was made. Automatic and semi-automatic image segmentation algorithms were proposed to extract the target microorganisms area, and 6 features were extracted. The model optimization problem of water microorganisms classification process was studied. First, the parameters of a few features were optimized. Then, all the features were fused, and a microorganisms recognition model of support vector machine optimized by particle swarm optimization (PSO-SVM) was established and compared with other recognition algorithms. The results show that, compared with the other 3 recognition algorithms, PSO-SVM can recognize different kinds of microorganisms more effectively, with an average recognition rate of 97.08%.