资源论文2D Image Analysis by Generalized Hilbert Transforms in Conformal Space*

2D Image Analysis by Generalized Hilbert Transforms in Conformal Space*

2020-03-30 | |  57 |   33 |   0

Abstract

This work presents a novel rotational invariant quadrature filter approach - called the conformal monogenic signal - for analyz- ing i(ntrinsic)1D and i2D local features of any curved 2D signal such as lines, edges, corners and junctions without the use of steering. The conformal monogenic signal contains the monogenic signal as a special case for i1D signals and combines monogenic scale space, phase, direc- tion/orientation, energy and curvature in one unified algebraic frame- work. The conformal monogenic signal will be theoretically illustrated and motivated in detail by the relation of the 3D Radon transform and the generalized Hilbert transform on the sphere. The main idea is to lift up 2D signals to the higher dimensional conformal space where the signal features can be analyzed with more degrees of freedom. Results of this work are the low computational time complexity, the easy imple- mentation into existing Computer Vision applications and the numerical robustness of determining curvature without the need of any derivatives.

上一篇:Real Time Feature Based 3-D Deformable Face Tracking

下一篇:Behind the Depth Uncertainty: Resolving Ordinal Depth in SFM*

用户评价
全部评价

热门资源

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...