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Wavelet-based Reflection Symmetry Detection via Textural and Color\n Histograms

2017/07/10 by Mohamed Elawady, Elawady, Mohamed, Christophe Ducottet +7 · 1 citation
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Remote-Sensing Image Classification

paper · pdf · doi:10.48550/arxiv.1707.02931

openalex publication_date 2017/07/10 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28

Abstract

Symmetry is one of the significant visual properties inside an image plane,\nto identify the geometrically balanced structures through real-world objects.\nExisting symmetry detection methods rely on descriptors of the local image\nfeatures and their neighborhood behavior, resulting incomplete symmetrical axis\ncandidates to discover the mirror similarities on a global scale. In this\npaper, we propose a new reflection symmetry detection scheme, based on a\nreliable edge-based feature extraction using Log-Gabor filters, plus an\nefficient voting scheme parameterized by their corresponding textural and color\nneighborhood information. Experimental evaluation on four single-case and three\nmultiple-case symmetry detection datasets validates the superior achievement of\nthe proposed work to find global symmetries inside an image.\n

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