ML Anthology

Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results

Mohamed Elawady, Christophe Ducottet, Olivier Alata, Cécile Barat, Philippe Colantoni
ICCVW 2017 pp. 1734-1738
doi:10.1109/ICCVW.2017.203 /iccvw/2017/elawady2017iccvw-waveletbased-a/

Abstract

The proposed algorithm detects globally the symmetry axes inside an image plane. The main steps are as follows: We firstly extract edge features using Log-Gabor filters with different scales and orientations. Afterwards, we use the edge characteristics associated with the textural and color information as symmetrical weights for voting triangulation. In the end, we construct a polar-based voting histogram based on the accumulation of the symmetry contribution (local texture and color information), in order to find the maximum peaks presenting as candidates of the primary symmetry axes.

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Cite

Text

Elawady et al. "Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results." IEEE/CVF International Conference on Computer Vision Workshops, 2017. doi:10.1109/ICCVW.2017.203

Markdown

[Elawady et al. "Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results." IEEE/CVF International Conference on Computer Vision Workshops, 2017.](https://mlanthology.org/iccvw/2017/elawady2017iccvw-waveletbased-a/) doi:10.1109/ICCVW.2017.203

BibTeX

@inproceedings{elawady2017iccvw-waveletbased-a,
  title     = {{Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results}},
  author    = {Elawady, Mohamed and Ducottet, Christophe and Alata, Olivier and Barat, Cécile and Colantoni, Philippe},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2017},
  pages     = {1734-1738},
  doi       = {10.1109/ICCVW.2017.203},
  url       = {https://mlanthology.org/iccvw/2017/elawady2017iccvw-waveletbased-a/}
}