Journal ArticleDOI
A distance metric for multidimensional histograms
TLDR
The problem of finding a translation to minimize the distance between point patterns is discussed and the sum of the distances in the minimal pairing is used as the “match distance” between the histograms.Abstract:
A metric is defined on the space of multidimensional histograms. Such histograms store in thexth location the number of events with feature vectorx; examples are gray level histograms and co-occurrence matrices of digital images. Given two multidimensional histograms, each is “unfolded” and a minimum distance pairing is performed using a distance metric on the feature vectorsx. The sum of the distances in the minimal pairing is used as the “match distance” between the histograms. This distance is shown to be a metric, and in the one-dimensional case is equal to the absolute difference of the two cumulative distribution functions. Among other applications, it facilitates direct computation of the distance between co-occurrence matrices or between point patterns. The problem of finding a translation to minimize the distance between point patterns is also discussed.read more
Citations
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Journal ArticleDOI
The Earth Mover's Distance as a Metric for Image Retrieval
TL;DR: This paper investigates the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval, and compares the retrieval performance of the EMD with that of other distances.
Proceedings ArticleDOI
A metric for distributions with applications to image databases
TL;DR: This paper uses the Earth Mover's Distance to exhibit the structure of color-distribution and texture spaces by means of Multi-Dimensional Scaling displays, and proposes a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.
Journal ArticleDOI
Shape distributions
TL;DR: The dissimilarities between sampled distributions of simple shape functions provide a robust method for discriminating between classes of objects in a moderately sized database, despite the presence of arbitrary translations, rotations, scales, mirrors, tessellations, simplifications, and model degeneracies.
Proceedings ArticleDOI
Fast and robust Earth Mover's Distances
Ofir Pele,Michael Werman +1 more
TL;DR: A new algorithm is presented for a robust family of Earth Mover's Distances - EMDs with thresholded ground distances so that the number of edges is reduced by an order of magnitude, which makes it possible to compute the EMD on large histograms and databases.
Proceedings ArticleDOI
Matching 3D models with shape distributions
TL;DR: The primary motivation for this approach is to reduce the shape matching problem to the comparison of probability distributions, which is simpler than traditional shape matching methods that require pose registration, feature correspondence or model fitting.
References
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Book
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Azriel Rosenfeld,Avinash C. Kak +1 more
TL;DR: The rapid rate at which the field of digital picture processing has grown in the past five years had necessitated extensive revisions and the introduction of topics not found in the original edition.
Journal ArticleDOI
Image Enhancement by Histogram transformation
TL;DR: In this article, a number of simple and inexpensive enhancement techniques are suggested to make use of easily computed local context, features to aid in the reassignment of each point's gray level during histogram transfomation.
Journal ArticleDOI
Texture Analysis Using Generalized Co-Occurrence Matrices
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