An algorithm combining Structured Occlusion Coding (SOC) with Extreme Learning Machine (ELM) was proposed to deal with the occlusion problem in face recognition. Firstly, the SOC was used to remove the occlusion from the image and separate the oclusion from the human face. At the same time, the position of the occlusion was estimated by the Local Constraint Dictionary (LCD), and an occlusion dictionary and a face dictionary were established. Then, the established face dictionary matrix was normalized, and the ELM was used to classify and identify the normalized data. Finally, the simulation results on the AR face database show that the proposed method has higher recognition rate and stronger robustness for different types of occlusions and images with different regions occluded.