A Framework For TV Logos Learning Using Linear Inverse Diffusion Filters For Noise Removal

Different logotypes represent significant cues for video annotations. A combination of temporal and spatial segmentation methods can be used for logo extraction from various video contents. To achieve this segmentation, pixels with low variation of intensity over time are detected. Static backgrounds can become spurious parts of these logos. This paper offers a new way to use several segmentations of logos to learn new logo models from which noise has been removed. First, we group segmented logos of similar appearances into different clusters. Then, a model is learned for each cluster that has a minimum number of members. This is done by applying a linear inverse diffusion filter to all logos in each cluster. Our experiments demonstrate that this filter removes most of the noise that was added to the logo during segmentation and it successfully copes with misclassified logos that have been wrongly added to a cluster

Fundamentos de los computadores

Los fundamentos, conceptos y modos de operación de estas máquinas tan comunes hoy en día, son los que tratamos de introducir y desentrañar en este texto. O con otras palabras, este libro está orientado a aquellas personas que alguna vez se han preguntado "¿Cómo es posible que los transistores y puertas lógicas que hay dentro de mi ordenador me permitan editar un archivo o ejecutar un programa que he escrito en Modula o en C?", pregunta, que por otro lado, esperamos se hayan planteado todos nuestros alumnos de asignaturas de introducción a los computadores. Aunque no son del todo necesarios, suponemos que el lector tiene algunos conocimientos de electrónica digital y programación. Pues bien, en este libro precisamente queremos cubrir el desnivel semántico que existe en un sistema computador entre esas dos materias (electrónica digital y lenguajes de alto nivel), contemplando el control microprogramado y cableado, el lenguaje ensamblador y los sistemas operativos, según desglosamos a continuación por temas

Low-textured regions detection for improving stereoscopy algorithms

The main goal of stereoscopy algorithms is the calculation of the disparity map between two frames corresponding to the same scene, and captured simultaneously by two different cameras. The different position (disparity) where common scene points are projected in both camera sensors can be used to calculate the depth of the scene point. Many algorithms calculate the disparity of corresponding points in both frames relying on the existence of similar textured areas around the pixels to be analyzed. Unfortunately, real images present large areas with low texture, which hinder the calculation of the disparity map. In this paper we present a method that employs a set of local textures to build a classifier that is able to select reliable pixels where the disparity can be accurately calculated, improving the precision of the scene map obtained by the stereoscopic technique.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Ministry of Education and Science of Spain under contract TIN2010-16144 and Junta de Andalucía under contract TIC-1692

An Experience of e-assessment in an Introductory Course on Computer Organization

This work describes how the CTPracticalsMoodle module can be used for e-assessment in an introductory course on computer organization, where the practical content consists of the design and simulation of a basic CPU implemented using Logisim, a schematic-based educational tool for the design and simulation of digital circuits. A previous work extended this module to support the verification of codes written in Matlab. This work shows how this feature can be exploited to invoke external tools, i.e. Logisim, not only for the automatic verification of the student submissions, but also for a detailed analysis of the results that improves the assessment. The paper will also present some customization of Logisim that was necessary to improve its batch mode simulation in order to add some useful options that make it generate a richer output format.Campus de Excelencia Internacional Andalucía Tech.Proyectos de Innovación Educativa PIE08-062 y PIE10-140. Universidad de Málaga

Pre-Ictal Phase Detection with SVMs

Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. There is a need for a quick screening process that could help neurologist diagnose and determine the patient’s treatment. Electroencephalogram has been traditionally used to diagnose patients by evaluating those brain functions that may correspond to epilepsy. The objective of this paper is to implement a novel detection technique of pre-ictal state that announces epileptic seizures from the online EEG data analysis. Unlike most published methods, that are aimed to distinguish only the normal from the epilepsy state, in this work the pre-ictal state is introduced as a new patient status, thus differentiating three possible states: normal (healthy), pre-ictal and epileptic seizure. In this manner, the patient should get timely alert about the possible seizure attack so that she/he can stop with its activities and take safety precautions.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This work is partially supported by the Ministry of Education and Science of Spain under contract TIN2010-16144 and Junta de Andalucía under contract TIC-1692