Ten lectures on wavelets
3-D Reconstruction Using Mirror Images Based on a Plane Symmetry Recovering Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast reflectional symmetry detection using orientation histograms
Real-Time Imaging - Special issue on real-time defect detection
Scientific Computing and Differential Equations: An Introduction to Numerical Methods
Scientific Computing and Differential Equations: An Introduction to Numerical Methods
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
EURASIP Journal on Applied Signal Processing
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Vision can be considered as a feature mining problem. Visually meaningful features are often geometrical, e.g., boundaries (or edges), corners, T-junctions, and symmetries. Mirror symmetry or near mirror symmetry is one of the most common and useful symmetry types in image and vision analysis. The current paper proposes several different approaches for studying 2-dimensional (2-D) mirror symmetric shapes. Proper mirror symmetry metrics are introduced based upon the Lebesgue measure, Hausdorff distance, as well as lower-dimensional feature sets. Theory and computation of these approaches and measures are developed, and numerical results are demonstrated.