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David Masip, & Jordi Vitria. (2004). Object Recognition using Boosted Adaptive Features..
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Oriol Pujol, Oriol Rodriguez-Leor, J. Mauri, E. Fernandez, V. Valle, & Petia Radeva. (2004). Automatic segmentation and characterization of IVUS images by texture analysis.
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O. Rodriguez, David Rotger, J. Mauri, E. Fernandez, V. Valle, & Petia Radeva. (2004). Active vessel workstation: three-dimensional reconstruction of coronary arteries by fusion of angiography and intravascular ultrasound.
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Jordi Vitria, Petia Radeva, & I. Aguilo. (2004). Recent Advances in Artificial Intelligence Research and Development. In Frontiers in Artificial Intelligence and Applications, 113, J. Vitria, P. Radeva, I. Aguilo (Eds.), ISBN: 1–58603–466–9.
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Philippe Dosch, & Josep Llados. (2004). Vectorial Signatures for Symbol Discrimination.
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Oriol Ramos Terrades, & Ernest Valveny. (2004). Indexing Technical Symbols Using Ridgelets Transform.
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Ernest Valveny, & Philippe Dosch. (2004). Symbol Recognition Contest: A Synthesis.
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Gemma Sanchez, & Josep Llados. (2004). Syntactic models to represent perceptually regular repetitive patterns in graphic documents.
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Angel Sappa. (2004). Automatic Extraction of Planar Projections from Panoramic Range Images.
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Angel Sappa. (2004). Surface Model Generation from Range Images of Industrial Environments.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & Michael G. Strintzis. (2004). Unsupervised Motion Classification by means of Efficient Feature Selection and Tracking.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & Michael G. Strintzis. (2004). 3D Gait Estimation from Monoscopic Video.
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Angel Sappa, & M.A. Garcia. (2004). Hierarchical Clustering of 3D Objects and its Application to Minimum Distance Computation. In IEEE International Conference on Robotics & Automation, 5287–5292, New Orleans, LA (USA), ISBN: 0–7803–8232–3.
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M.A. Garcia, & Angel Sappa. (2004). Efficient Generation of Discontinuity-Preserving Adaptive Triangulations from Range Images. IEEE Trans. on Systems, Man, and Cybernetics (Part B), 34(5):2003–2014 (IF: 1.052).
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Debora Gil, & Petia Radeva. (2004). A Regularized Curvature Flow Designed for a Selective Shape Restoration. IEEE Transactions on Image Processing, 13, 1444–1458.
Abstract: Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization.
Keywords: Geometric flows, nonlinear filtering, shape recovery.
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