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Curved Glide-Reflection Symmetry Detection
February 2012 (vol. 34 no. 2)
pp. 266-278
ASCII Text
x 
 
Seungkyu Lee, Yanxi Liu, "Curved Glide-Reflection Symmetry Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 2, pp. 266-278, February, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2011.118,
author = { Seungkyu Lee and Yanxi Liu},
title = {Curved Glide-Reflection Symmetry Detection},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {34},
number = {2},
issn = {0162-8828},
year = {2012},
pages = {266-278},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.118},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Curved Glide-Reflection Symmetry Detection
IS - 2
SN - 0162-8828
SP266
EP278
EPD - 266-278
A1 - Seungkyu Lee,
A1 - Yanxi Liu,
PY - 2012
KW - image segmentation
KW - computer vision
KW - feature extraction
KW - saliency detection
KW - curved glide reflection symmetry detection
KW - bilateral reflection symmetry
KW - 2D euclidean space
KW - feature based approach
KW - unsegmented 2D images
KW - axis parameter space
KW - APS
KW - computer vision
KW - biomedical imaging
KW - Three dimensional displays
KW - Detection algorithms
KW - Feature extraction
KW - Computer vision
KW - Image edge detection
KW - Algorithm design and analysis
KW - curved surface.
KW - Symmetry
KW - glide reflection
KW - curved axis
VL - 34
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Seungkyu Lee, Adv. Media Lab., Samsung Adv. Inst. of Technol. (SALT), Yongin, South Korea
Yanxi Liu, Dept. of Comput. Sci. & Electr. Eng., Pennsylvania State Univ., University Park, PA, USA
We generalize the concept of bilateral reflection symmetry to curved glide-reflection symmetry in 2D euclidean space, such that classic reflection symmetry becomes one of its six special cases. We propose a local feature-based approach for curved glide-reflection symmetry detection from real, unsegmented 2D images. Furthermore, we apply curved glide-reflection axis detection for curved reflection surface detection in 3D images. Our method discovers, groups, and connects statistically dominant local glide-reflection axes in an Axis-Parameter-Space (APS) without preassumptions on the types of reflection symmetries. Quantitative evaluations and comparisons against state-of-the-art algorithms on a diverse 64-test-image set and 1,125 Swedish leaf-data images show a promising average detection rate of the proposed algorithm at 80 and 40 percent, respectively, and superior performance over existing reflection symmetry detection algorithms. Potential applications in computer vision, particularly biomedical imaging, include saliency detection from unsegmented images and quantification of deviations from normality. We make our 64-test-image set publicly available.

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Index Terms:
image segmentation,computer vision,feature extraction,saliency detection,curved glide reflection symmetry detection,bilateral reflection symmetry,2D euclidean space,feature based approach,unsegmented 2D images,axis parameter space,APS,computer vision,biomedical imaging,Three dimensional displays,Detection algorithms,Feature extraction,Computer vision,Image edge detection,Algorithm design and analysis,curved surface.,Symmetry,glide reflection,curved axis
Citation:
Seungkyu Lee, Yanxi Liu, "Curved Glide-Reflection Symmetry Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 2, pp. 266-278, Feb. 2012, doi:10.1109/TPAMI.2011.118
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