On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
Orthogonal Moment Features for Use With Parametric and Non-Parametric Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Radon Transform Orientation Estimation for Rotation Invariant Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward accurate dynamic time warping in linear time and space
Intelligent Data Analysis
Selection of Suitable Set of Decision Rules Using Choquet Integral
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Farthest point distance: A new shape signature for Fourier descriptors
Image Communication
A new shape descriptor defined on the Radon transform
Computer Vision and Image Understanding
Using Spatial Relations for Graphical Symbol Description
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Gait Recognition Using Radon Transform and Linear Discriminant Analysis
IEEE Transactions on Image Processing
Similarity search for time series based on efficient warping measure
DM-IKM '12 Proceedings of the Data Mining and Intelligent Knowledge Management Workshop
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In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. This allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.