
Proceedings Paper
Logo recognition using alpha-rooted phase correlation in the radon transform domainFormat | Member Price | Non-Member Price |
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Paper Abstract
Alpha-rooted phase correlation (ARPC) is a recently-developed variant of classical phase correlation that includes a
Fourier domain image enhancement operation. ARPC combines classical phase correlation with alpha-rooting to provide
tunable image enhancement. The alpha-rooting parameters may be adjusted to provide a tradeoff between height and
width of the ARPC main lobe. A high narrow main lobe peak provides high matching accuracy for aligned images, but
reduced matching performance for misaligned logos. A lower, wider peak trades matching accuracy on aligned logos, for
improved matching performance on misaligned imagery. Previously, we developed ARPC and used it in the spatial
domain for logo recognition as part of an overall automated document analysis problem. However, spatial domain ARPC
performance can be sensitive to logo misalignments, including rotational misalignment. In this paper we use ARPC as a
match metric in the radon transform domain for logo recognition. In the radon transform domain, rotational
misalignments correspond to translations in the radon transform angle parameter. These translations are captured by
ARPC, thereby producing rotation-invariant logo matching. In the paper, we first present an overview of ARPC, and
then describe the logo matching algorithm. We present numerical performance results demonstrating matching tolerance
to rotational misalignments. We demonstrate robustness of the radon transform domain rotation estimation to noise. We
present logo verification and recognition performance results using the proposed approach on a public domain logo
database. We compare performance results to performance obtained using spatial domain ARPC, and state-of-the-art
SURF features, for logos in salt-and-pepper noise.
Paper Details
Date Published: 2 September 2009
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 744305 (2 September 2009); doi: 10.1117/12.824692
Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 744305 (2 September 2009); doi: 10.1117/12.824692
Show Author Affiliations
Stephen DelMarco, BAE Systems (United States)
Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)
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