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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 594)
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About this book
The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract useful image features and how to use them for intuitive retrieval. We present a novel approach to the problem of navigating through a collection of images for the purpose of image retrieval, which leads to a new paradigm for image database search. We summarize the appearance of images by distributions of color or texture features, and we define a metric between any two such distributions. This metric, which we call the "Earth Mover's Distance" (EMD), represents the least amount of work that is needed to rearrange the mass is one distribution in order to obtain the other. We show that the EMD matches perceptual dissimilarity better than other dissimilarity measures, and argue that it has many desirable properties for image retrieval. Using this metric, we employ Multi-Dimensional Scaling techniques to embed a group of images as points in a two- or three-dimensional Euclidean space so that their distances reflect image dissimilarities as well as possible. Such geometric embeddings exhibit the structure in the image set at hand, allowing the user to understand better the result of a database query and to refine the query in a perceptually intuitive way.
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Table of contents (8 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Perceptual Metrics for Image Database Navigation
Authors: Yossi Rubner, Carlo Tomasi
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/978-1-4757-3343-3
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag US 2001
Hardcover ISBN: 978-0-7923-7219-6Published: 31 December 2000
Softcover ISBN: 978-1-4419-4863-2Published: 06 December 2010
eBook ISBN: 978-1-4757-3343-3Published: 14 March 2013
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XXIII, 137
Topics: Control, Robotics, Mechatronics, Artificial Intelligence, Image Processing and Computer Vision, Data Structures and Information Theory