Texture discrimination by Gabor functions
Biological Cybernetics
The design and analysis of spatial data structures
The design and analysis of spatial data structures
International Journal of Computer Vision
Multimedia information systems: issues and approaches
Modern database systems
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Distance-based indexing for high-dimensional metric spaces
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
Multimedia Tools and Applications
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
Content-Based Indexing of Multimedia Databases
IEEE Transactions on Knowledge and Data Engineering
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Near Neighbor Search in Large Metric Spaces
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Generalized Search Trees for Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
CMVF: a novel dimension reduction scheme for efficient indexing in a large image database
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
WARP: Accurate Retrieval of Shapes Using Phase of Fourier Descriptors and Time Warping Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Active Vertice method: a performant filtering approach to high-dimensional indexing
Data & Knowledge Engineering
Toward Efficient Multifeature Query Processing
IEEE Transactions on Knowledge and Data Engineering
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
Efficient benchmarking of content-based image retrieval via resampling
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Knowledge discovery in multimedia repositories: the role of metadata
MMACTE'05 Proceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering
Indexing text and visual features for WWW images
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
TempoM2: a multi feature index structure for temporal video search
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Color recognition with compact color features
International Journal of Communication Systems
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The optimized distance-based access methods currently available for multidimensional indexing in multimedia databases have been developed based on two major assumptions: a suitable distance function is known a priori and the dimensionality of the image features is low. It is not trivial to define a distance function that best mimics human visual perception regarding image similarity measurements. Reducing high-dimensional features in images using the popular principle component analysis (PCA) might not always be possible due to the non-linear correlations that may be present in the feature vectors. We propose in this paper a fast and robust hybrid method for non-linear dimensions reduction of composite image features for indexing in large image database. This method incorporates both the PCA and non-linear neural network techniques to reduce the dimensions of feature vectors so that an optimized access method can be applied. To incorporate human visual perception into our system, we also conducted experiments that involved a number of subjects classifying images into different classes for neural network training. We demonstrate that not only can our neural network system reduce the dimensions of the feature vectors, but that the reduced dimensional feature vectors can also be mapped to an optimized access method for fast and accurate indexing.