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Felipe Lumbreras, Joan Serrat, Ramon Baldrich, Maria Vanrell, & Juan J. Villanueva. (2001). Color Texture Recognition Through Multiresolution Features.
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X. Orriols, Lluis Barcelo, & X. Binefa. (2001). Polynomial Fiber Description of Motion for Video Mosaicing, Proceeding ICIP 2001..
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X. Binefa, Jordi Vitria, & Xavier Roca. (1993). Deteccion de profundidad en imagenes monoculares mediante vision activa..
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A. Pujol, Jose Luis Alba, & Juan J. Villanueva. (2001). Supervised Hausdorff-based measures for face recognition..
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A. Pujol, Alex Caralps, & Juan J. Villanueva. (2001). On the suitability of pixel-outlier removal in face recognition..
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David Rotger, Cristina Cañero, Petia Radeva, J. Mauri, E. Fernandez, A. Tovar, et al. (2001). 3D Interactive Visualization and Volumetric Measurements of Coronary Vessels in IVUS..
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David Rotger, Cristina Cañero, Petia Radeva, J. Mauri, E. Fernandez, A. Tovar, et al. (2001). Advanced Visualization of 3D data of Intravascular Ultrasound Images..
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Petia Radeva, & Jordi Vitria. (2001). Region Based Approach for Discriminant Snakes..
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Gemma Sanchez, Josep Llados, & K. Tombre. (2001). An Algorithm to Recognize Graphical Textured Symbols using String Representations..
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Petia Radeva. (1993). A Rule-Based Approach to Hand X-Ray image Segmentation..
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Antonio Lopez, David Lloret, Joan Serrat, & Juan J. Villanueva. (2000). Multilocal Creaseness Based on the Level-Set Extrinsic Curvarture..
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Petia Radeva. (1993). Segmentacion de Imagenes Radiograficas con Snakes. Aplicacion a la Determinacion de la Madurez Osea..
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V. Valev, & Petia Radeva. (1993). On the Determining of Non-Reducible Descriptors for Multidimensional Pattern Recognition Problems..
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Josep Llados, & Enric Marti. (1999). A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems..
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David Lloret, Antonio Lopez, Joan Serrat, & Juan J. Villanueva. (1999). Creaseness-based computer tomography and magnetic resonance registration: Comparison with the mutual information method..
Abstract: This paper describes a method which uses the skull as a landmark for automatic registration of computer tomography to magnetic resonance (MR) images. First, the skull is extracted from both images using a new creaseness operator. Then, the resulting creaseness images are used to build a hierarchic structure which permits a robust and fast search. We have justified experimentally the performance of several choices of our algorithm, and we have thoroughly tested its accuracy and robustness against the well-known mutual information method for five different pairs of images. We have found both comparable, and for certain MR images the proposed method achieves better performance.
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