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Scale Invariant Feature Transform for n-Dimensional Images (n-SIFT)

Cheung, Warren, Hamarneh, Ghassan
University of British Columbia
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1321
New: Prefer using the following doi: https://doi.org/10.54294/tiqso5
Published in The Insight Journal - 2007 July - December.
Submitted by Warren Cheung on 2007-12-01T00:00:00Z.

This document describes the implementation of several features previously developed[2], extending the 2D scale invariant feature transform (SIFT)[4, 5] for images of arbitrary dimensionality, such as 3D medical image volumes and time series, using ITK1. Specifically, we provide a scale invariant implementation of a weighted histogram of gradient feature, a rotationally invariant version of the histogram feature, and a SIFT-like feature, adapted to handle images of arbitrary dimensionality. This paper is accompanied with the source code, example input data, parameters and output data, allowing reproduction of the example results in this paper and the results previously reported[2]. Note that usage of SIFT in the United States is governed by US Patent 6,711,293.