Studies On The Hierarchical Data Processing In Pattern Classification And Visual Navigation

Theories related to hierarchical data processing of soft computing are hot topics in the past several years, such as granular computing, multi-resolution analysis, multi-scale analysis, etc. By representing the universe of the problem in different granulation (resolution, scale), it provides a possibility to solve problems more easy, make problems solvable which can not be solved in the original universe, and reduce the computational complexity. In this dissertation, we study the application of hierarchical data processing to pattern classification and visual navigation. Results of the research are helpful to large scale data classification and analysis the content of image.The first part of this dissertation discusses the relationship between multi-granule representation and processing with pattern classification. Research results can be summarized as follows. (1) By analyzing four kinds of risk minimization principles, the relationship between the size of the training data set and the trained classifier, and the possibility of combining the pattern classification with hierarchical data processing, it shows that the classification problem may be solved efficiently by representing the data set in coarse granulation. (2) An area based risk minimization principle is proposed. By representing the samples set by hyper-sphere (or hyper-cube), the boundary location can be controlled by the center and radius of the area. Experimental results show that the method proposed in this paper can reduce both the number of the training samples set and the support vectors. (3) We propose a multi-resolution classification strategy based on the partition of feature space. The training algorithm locates the boundary between two classes from coarse to fine resolutions by dividing the hyper-cuboids that lie on the boundary step by step. The testing algorithm firstly labels the testing data set by the classifier trained at initial resolution. Then only those lying on the boundary will be labeled at the finer resolution. Theoretical analysis and...