期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2015
卷号：6
期号：1
页码：13
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In most practical applications of image retrieval, high-dimensional feature vectors are required, butcurrent multi-dimensional indexing structures lose their efficiency with growth of dimensions. Our goal isto propose a divisive hierarchical clustering-based multi-dimensional indexing structure which is efficientin high-dimensional feature spaces. A projection pursuit method has been used for finding a component ofthe data, which data's projections onto it maximizes the approximation of negentropy for preparingessential information in order to partitioning of the data space. Various tests and experimental results onhigh-dimensional datasets indicate the performance of proposed method in comparison with others.
