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http://hdl.handle.net/1893/31708| Appears in Collections: | Computing Science and Mathematics Conference Papers and Proceedings |
| Author(s): | Elawady, Mohamed Ducottet, Christophe Alata, Olivier Barat, Cecile Colantoni, Philippe |
| Contact Email: | mohamed.elsayed.elawady@stir.ac.uk |
| Title: | Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results |
| Citation: | Elawady M, Ducottet C, Alata O, Barat C & Colantoni P (2017) Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms: Algorithm and Results. In: 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), Venice, Italy, 22.10.2017-29.10.2017. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/iccvw.2017.203 |
| Issue Date: | Oct-2017 |
| Date Deposited: | 22-Sep-2020 |
| Conference Name: | 2017 IEEE International Conference on Computer Vision Workshop (ICCVW) |
| Conference Dates: | 2017-10-22 - 2017-10-29 |
| Conference Location: | Venice, Italy |
| 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. |
| Status: | VoR - Version of Record |
| Rights: | The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 10.1109ICCVW.2017.203.pdf | Fulltext - Published Version | 393.31 kB | Adobe PDF | View/Open |
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