IEEE Transactions on Pattern Analysis and Machine Intelligence
Applying algebraic and differential invariants for logo recognition
Machine Vision and Applications
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
Fingerprint Matching With Rotation-Descriptor Texture Features
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
A Review of Shape Descriptors for Document Analysis
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
A new shape descriptor defined on the Radon transform
Computer Vision and Image Understanding
Invariant pattern recognition using the RFM descriptor
Pattern Recognition
Rotation-invariant multiresolution texture analysis using Radon and wavelet transforms
IEEE Transactions on Image Processing
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A shape descriptor combining the Radon transform, the amplitude extraction, and the log-mapping is proposed in this paper. It is invariant to shape rotation, scaling, and translation. Invariance to translation is achieved by amplitude extraction on the radial coordinate. Rotation and scaling are log-mapped into two-dimensional translations and recovered with the phase-only correlation function. In addition, all transformation parameters (rotating angle, scaling factor, and position shift) can be determined also. The efficiency of the proposed descriptor compared to existing methods is shown experimentally on different kind of datasets.