Abstract
In most practical applications of image retrieval, high-dimensional feature vectors are required, but current multi-dimensional indexing structures lose their efficiency with growth of dimensions. Our goal is to propose a divisive hierarchical clustering-based multi-dimensional indexing structure which is efficient in high-dimensional feature spaces. A projection pursuit method has been used for finding a component of the data, which data's projections onto it maximizes the approximation of negentropy for preparing essential information in order to partitioning of the data space. Various tests and experimental results on high-dimensional datasets indicate the performance of proposed method in comparison with others.
Highlights
Due to the advances in hardware technology and increase in the production of digital images in various applications, it is necessary to develop efficient techniques for storing and retrieval of such images [1, 2, 3]
In contentbased image retrieval approach, visual features such as colour feature, texture feature, shape feature and local features are automatically extracted from the image objects and organized as feature vectors
Multidimensional indexing structures have been used for organization of multi-dimensional image features and searching image database has been done via multi-dimensional indexing structure for having appropriate speed in retrieval process [5, 6, 7]
Summary
Due to the advances in hardware technology and increase in the production of digital images in various applications, it is necessary to develop efficient techniques for storing and retrieval of such images [1, 2, 3]. One of the discussed issues in content-based image retrieval research area is to use efficient methods to accelerate search operation in image retrieval databases. For this purpose, multidimensional indexing structures have been used for organization of multi-dimensional image features and searching image database has been done via multi-dimensional indexing structure for having appropriate speed in retrieval process [5, 6, 7]. It is shown that in high-dimensional data spaces, multi-dimensional indexing structures tend to perform worse than the sequential scanning of the database.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Signal & Image Processing : An International Journal
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
