According to the existence of motif in complex network topology structure, the motif-based node degree and edge degree are proposed to measure the importance of node and edge in the network on the basis of the traditional node degree and edge clustering coefficient. The Rand-ESU algorithm is used for motif detection of eight different scale networks, and the result demonstrates the existence of motif. The Rand-ESU algorithm is also used for analyzing the motif structures and characteristics in Karate network and Dolphin network. The Pearson correlation coefficient is used to measure the correlations of motif-based node degree and traditional node degree, motif-based edge degree and edge clustering coefficient. The results of simulation analysis show that the correlations are related to the motif species. The definitions of motif-based node degree and edge degree are the improvement and development of original definitions, and they comprehensively depict the importance of node and edge in the network.