Unsupervised level set parameterization using multi-scale filtering
Ημερομηνία
2013ISBN
978-1-4673-5805-7Source
2013 18th International Conference on Digital Signal Processing, DSP 20132013 18th International Conference on Digital Signal Processing, DSP 2013
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Εμφάνιση πλήρους εγγραφήςΕπιτομή
This paper presents a novel framework for unsupervised level set parameterization using multi-scale filtering. A standard multi-scale, directional filtering algorithm is used in order to capture the orientation coherence in edge regions. The latter is encoded in entropy-based image 'heatmaps', which are able to weight forces guiding level set evolution. Experiments are conducted on two large benchmark databases as well as on real proteomics images. The experimental results demonstrate that the proposed framework is capable of accelerating contour convergence, whereas it obtains a segmentation quality comparable to the one obtained with empirically optimized parameterization. © 2013 IEEE.