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Jordi Vitria, Petia Radeva, X. Binefa, A. Pujol, Ernest Valveny, Robert Benavente, et al. (1999). Real time recognition of pharmaceutical products by subspace methods.
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Jorge Bernal. (2009). Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction (Vol. 141). Master's thesis, , Barcelona, Spain.
Abstract: One of the biggest drawbacks related to the use of CT scanners is the cost (in memory and in time) associated. In this project many methods to simulate their functioning, but in a more feasible way (taking an industrial point of view), will be studied.
The main group of techniques that are being used are the one entitled as ’back-projection’. The concept behind is to simulate the X ray emission in CT scans by lines that cross with the image we want to reconstruct.
In the first part of this document euclidean geometry is used to face the tasks of projec- tion and back-projection. After analysing the results achieved it has been proved that this approach does not lead to a fully perfect reconstruction (and also has some other problems related to running time and memory cost). Because of this in the second part of the document ’Filtered Back-projection’ method is introduced in order to improve the results.
Filtered Back-projection methods rely on mathematical transforms (Fourier, Radon) in order to provide more accurate results that can be obtained in much less time. The main cause of this better results is the use of a filtering process before the back-projection in order to avoid high frequency-caused errors.
As a result of this project two different implementations (one for each approach) had been implemented in order to compare their performance.
Keywords: Projection, Back-projection, CT scan, Euclidean geometry, Radon transform
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Jorge Bernal, Fernando Vilariño, & F. Javier Sanchez. (2010). Feature Detectors and Feature Descriptors: Where We Are Now (Vol. 154).
Abstract: Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours.
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Jose Antonio Rodriguez. (2006). Pen-based Interfaces and Recognition: Application to Proofreading Interpretation.
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Jose Carlos Rubio. (2009). Graph matching based on graphical models with application to vehicle tracking and classification at night (Vol. 144). Master's thesis, , Bellaterra, Barcelona.
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Jose Manuel Alvarez. (2007). On-Board Road Surface Segmentation.
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Josep Llados. (1996). Interpretacio de dibuixos linials fets a ma alçada mitjançant isomorfisme entre subgrafs i transformacio de Hough.
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Josep M. Gonfaus. (2009). Semantic Segmentation of Images Using Random Ferns (Vol. 132). Master's thesis, , Bellaterra, Barcelona.
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Juan Diego Gomez. (2009). Toward Robust Myocardial Blush Grade Estimation in Contrast Angiography (Vol. 134). Master's thesis, , Bellaterra, Barcelona.
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Karla Lizbeth Caballero. (2007). Coronary Plaque Classification using Intravascular Ultrasound Images and Radio Frequency Signals.
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Laura Ruiz. (2007). Methods about Pattern Recognition.
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Lluis Barcelo. (2002). Accurate video mosaicing with moving objects.
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Lluis Gomez. (2012). Perceptual Organization for Text Extraction in Natural Scenes (Vol. 173). Master's thesis, , .
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Lluis Pere de las Heras. (2010). Syntactic Model for Semantic Document Analysis (Vol. 158).
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M. Bressan. (2001). Un analisis de viabilidad para la confeccion semisupervisada de un mapa de usos del suelo de Catalunya.
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