Applied multivariate statistical analysis
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Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Floating search methods in feature selection
Pattern Recognition Letters
Interactive learning of a multiple-attribute hash table classifier for fast object recognition
Computer Vision and Image Understanding
An optimal algorithm for approximate nearest neighbor searching
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
ACM Computing Surveys (CSUR)
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modern Information Retrieval
Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences
Using human perceptual categories for content-based retrieval from a medical image database
Computer Vision and Image Understanding
ImageRover: A Content-Based Image Browser for the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Multidimensional Binary Search Trees in Database Applications
IEEE Transactions on Software Engineering
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Modeling multi-object spatial relationships for satellite image database indexing and retrieval
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
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In this paper we present a new image database indexing structure - Entropy Balanced Statistical (EBS) k-d Tree. This indexing mechanism utilizes the statistical properties and ground-truth labeling of image data for efficient and accurate searches. It is particularly valuable in the domains of medical and biological image database retrieval, where ground-truth labeling are available and archived with the images. The EBS k-d tree is an extension to the statistical k-d tree that attempts to optimize a multi-dimensional decision tree based on the fundamental principles from which it is constructed. Our approach is to develop and validate the notion of an entropy balanced statistical based decision tree. It is shown that by making balanced split decisions in the growth processing of the tree, that the average search depth is improved and the worst case search depth is usually dramatically improved. Furthermore, a method for linking the tree leaves into a non-linear structure was developed to increase the n-nearest neighbor similarity search accuracy. We have applied this to a large-scale medical diagnostic image database and have shown increases in search speed and accuracy over an ordinary distance-based search and the original statistical k-d tree index.