A dynamic background compensation method based on speeded-up robust f eatures (SURF) and fast retina keypoint (FREAK) algorithm is proposed in this paper to solve the problem of background deviation and lack of real time ability when detecting moving target with mobile terminal. Considering the redundancy degree of SURF algorithm in feature description phase and the deficiency of FREAK algorithm in feature detection.the two algorithms a re combined to complement each other to get the best results.Firstly,the SURF al gorithm is used to detect feature points and the FREAK algorithm is used to describe the feature points.Th en hamming distance matching is performed on feature points.and the last random sample consensus (RANSAC) algorithm is used to eliminate mismatched points.The b ackground compensation experiment based on mobile terminal is designed.The resul ts show that under different rotation angles,lighting conditions and sizes,compared with the SURF algorithm,the speed of this algorithm is impro ved by about four times,and the matching accuracy is basically 95%,which is much higher than that of FREAK algorithm,showing good matching effect and real-t ime performance.