Three-Dimension building modeling improves the visualization and applications of a city environment. Model-driven methods set up pre-designed models first, and then match models with data to estimate model parameters. One of the main challenges in this context is to choose the pre-designed models automatically. To achieve this goal, roof template matching is one of the ways. For matching purpose, the unique features of each object needs to be extracted first and then used for recognition. This paper presents two methods for obtaining the features which are Geometric moments and Zernike moments. In this research, we compare and discuss the results using both of them. The experiments show the feasibility of the generated features to recognize different type roofs. The discussion also covers the existence of noises that affect the results of generated features.