A new multi-feature cascade object matching （MFCM） method was proposed. Some previous works provided some object matching methods based on geometry feature. However, the complexity of these methods was too high. The key idea the MFCM method is that using the image feature to build the potential matching set for each point and then do the matching process twice： firstly, using the geometry feature to find the exactly corresponding point and add them to the ＂Result Set＂, through the geometry matching process, a vote mechanism was used to ensure the correctness; secondly, building the correspondence between the model point set and result set. The new method has both higher efficiency and correction than other geometry method. The results of experiments show that this new method can deal with the object matching problem with large amount of data.
NETL
NSTL
万方数据
维普
