Particles shape analysis and classification using the wavelet transform
Pattern Recognition Letters
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Digital Image Processing
Multiscale Fourier Descriptor for Shape Classification
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Scale-Space Behavior of Planar-Curve Corners
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic edge tracing: Boundary identification in medical images
Computer Vision and Image Understanding
Fourier Descriptors for Plane Closed Curves
IEEE Transactions on Computers
Overcomplete discrete wavelet transforms with rational dilation factors
IEEE Transactions on Signal Processing
Time-scale atoms chains for transients detection in audio signals
IEEE Transactions on Audio, Speech, and Language Processing
Filtering random noise from deterministic signals via datacompression
IEEE Transactions on Signal Processing
Sparse and structured decompositions of signals with the molecular matching pursuit
IEEE Transactions on Audio, Speech, and Language Processing
Singularity detection and processing with wavelets
IEEE Transactions on Information Theory - Part 2
Wavelet descriptor of planar curves: theory and applications
IEEE Transactions on Image Processing
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Abstract: This paper presents a novel approach for the local analysis of the contour of a planar real world shape. The 1D representation of that contour is a very complicated signal with several non isolated and oscillating singularities, which represent the micro-structure of the shape. The analysis of such a signal is usually difficult because of the presence of spurious phenomena in its time-scale representation, typical of oscillating singularities. The aim of the proposed model is to exploit the time-scale behavior of the energy of wavelet coefficients to extract a particular sequence of scales where those spurious phenomena are strongly reduced. The locality of the wavelet transform is then used to segment the contour into meaningful subregions, in agreement with their local spectral properties. Experimental results show that the proposed model overcomes some limits of existing methods for the analysis of real-world shapes micro-structure.