Conference Paper (published)
Details
Citation
Elawady M, Ducottet C, Alata O, Barat C & Colantoni P (2017) Wavelet-Based Reflection Symmetry Detection via Textural and Color Histograms. In: 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), Venice, 22.10.2017-29.10.2017. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/iccvw.2017.202
Abstract
Symmetry is one of the significant visual properties inside an image plane, to identify the geometrically balanced structures through real-world objects. Existing symmetry detection methods rely on descriptors of the local image features and their neighborhood behavior, resulting incomplete symmetrical axis candidates to discover the mirror similarities on a global scale. In this paper, we propose a new reflection symmetry detection scheme, based on a reliable edge-based feature extraction using Log-Gabor filters, plus an efficient voting scheme parameterized by their corresponding textural and color neighborhood information. Experimental evaluation on four single-case and three multiple-case symmetry detection datasets validates the superior achievement of the proposed work to find global symmetries inside an image.
Keywords
Feature extraction; Image edge detection; Image color analysis; Histograms; Frequency-domain analysis; Color
| Status | Published |
|---|---|
| Publication date | 31/10/2017 |
| URL | |
| Publisher | IEEE |
| Place of publication | Piscataway, NJ, USA |
| ISSN of series | 2473-9944 |
| ISBN | 9781538610343 |
| Conference | 2017 IEEE International Conference on Computer Vision Workshop (ICCVW) |
| Conference location | Venice |
| Dates | – |