In order to improve the accuracy of micro-expression recognition in video recognition field, a micro-expression recognition algorithm based on long short-term memory network and feature fusion is proposed. Both color features and texture features of micro expression images are extracted, and the selected spatial features are delivered to convolution neural networks for fusion. A new long short-term memory network is designed to learn temporal correlation between spatial features, the fused features are delivered to long short-term memory network to learn temporal features of micro expressions, the long short-term memory network is connected to classification network to recognize the class labels for each micro expression. Validation experiments are carried on two public micro expression recognition datasets, the results show that the proposed algorithm realizes better micro expression recognition performance, it realizes accuracy of 64.7% and 65.8% on SMIC dataset and CASME Ⅱ dataset, respectively.