Abstract:

A new method, named mixHausdorf distance, was designed to measure the similarity amongst packages. It can improve the performance of a classic multiinstance algorithm called CitationKNN. According to trees’ distinct imaging features, the paper analyzed the difficulty of handling trees graphs. Using wavelet transformation handling technique, a specialized method for generating the feature vector of tree images was proposed in order to make the improved algorithm identify the trees effectively. Our experiment proved that, compared with the main existing algorithms, the proposed algorithm has best effect for trees classification and good results when testing the recognized dataset.      

Key words: multi-instances learning;CitationKNN;mix-Hausdorf distance;trees classification