Multiscale Fourier descriptors for defect image retrieval
Pattern Recognition Letters
On Signature Invariants for Effective Motion Trajectory Recognition
International Journal of Robotics Research
2D shape classification and retrieval
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Shape classification via image-based multiscale description
Pattern Recognition
Original Articles: Time-scale energy based analysis of contours of real-world shapes
Mathematics and Computers in Simulation
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The description of the object shape is an important characteristic of the image. In image processing and pattern recognition, several different shape descriptors are used. In human visual perception, the shapes are processed in multiple resolutions. Therefore multiscale shape representation is essential in the shape based image classification and retrieval. In the description of the object shape, the multiresolution representation provides also additional accuracy to the shape classification.In this paper we introduce a new descriptor for shape classification. This descriptor is called multiscale Fourier descriptor, and it combines the benefits of Fourier descriptor and multiscale shape representation. This descriptor is formed by applying Fourier transform to thecoefficients of wavelet transform of the object boundary. In this way the Fourier descriptor can be presented in multiple resolutions.We make classification experiments using three image databases. The classification results of our method are compared to those of Fourier descriptors.