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Detecting Intrinsically Two-Dimensional Image Structures Using Local Phase

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Pattern Recognition (DAGM 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4174))

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Abstract

This paper presents a novel approach towards detecting intrinsically two-dimensional (i2D) image structures using local phase information. The local phase of the i2D structure can be derived from a curvature tensor and its conjugate part in a rotation-invariant manner. By employing damped 2D spherical harmonics as basis functions, the local phase is unified with a scale concept. The i2D structures can be detected as points of stationary phases in this scale-space by means of the so call phase congruency. As a dimensionless quantity, phase congruency has the advantage of being invariant to illumination change. Experiments demonstrate that our approach outperforms Harris and Susan detectors under the illumination change and noise contamination.

This work was supported by German Research Association (DFG) Graduiertenkolleg No. 357 (Di Zang) and DFG grant So-320/2-3 (Gerald Sommer).

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Zang, D., Sommer, G. (2006). Detecting Intrinsically Two-Dimensional Image Structures Using Local Phase. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_23

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  • DOI: https://doi.org/10.1007/11861898_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44412-1

  • Online ISBN: 978-3-540-44414-5

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