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Fast Computation of Rotation-Invariant Image Features by an Approximate Radial Gradient Transform

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6 Author(s)
Gabriel Takacs ; Microsoft Corporation, Sunnyvale, CA, USA ; Vijay Chandrasekhar ; Sam S. Tsai ; David Chen
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We present the radial gradient transform (RGT) and a fast approximation, the approximate RGT (ARGT). We analyze the effects of the approximation on gradient quantization and histogramming. The ARGT is incorporated into the rotation-invariant fast feature (RIFF) algorithm. We demonstrate that, using the ARGT, RIFF extracts features 16× faster than SURF while achieving a similar performance for image matching and retrieval.

Published in:

IEEE Transactions on Image Processing  (Volume:22 ,  Issue: 8 )