Search results for " Segmentation"
showing 10 items of 462 documents
A simple and efficient face detection algorithm for video database applications
2000
The objective of this work is to provide a simple and yet efficient tool to detect human faces in video sequences. This information can be very useful for many applications such as video indexing and video browsing. In particular the paper focuses on the significant improvements made to our face detection algorithm presented by Albiol, Bouman and Delp (see IEEE Int. Conference on Image Processing, Kobe, Japan, 1999). Specifically, a novel approach to retrieve skin-like homogeneous regions is presented, which is later used to retrieve face images. Good results have been obtained for a large variety of video sequences. Peer Reviewed
Three-dimensional cardiac computational modelling: methods, features and applications
2015
[EN] The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty …
Exploring the tourism markets’ convergence hypothesis in Italy
2020
This article aims at investigating the tourism markets’ convergence hypothesis across Italy’s 20 major source markets. To reach our goal, we use monthly data of tourist arrivals and overnights over the period 2008–2018 and the time-varying factor model developed by Phillips and Sul (2007, 2009). Our findings suggest the absence of full (absolute) convergence, leading us to accept the hypothesis of club convergence. We show that the traditionally more important source markets have a tendency to persist, while Asian countries show heterogeneous behaviour. Furthermore, the relative decline in the contribution to total arrivals and overnights of several international source markets calls for a…
Unsupervised clustering method for pattern recognition in IIF images
2017
Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy…
La segmentación territorial de la oferta comercial en las áreas turísticas de litoral : una propuesta metodológica
2021
Fundación CajaCanarias La modalidad y la categoría de los alojamientos turísticos se plantean como esenciales en la localización y la tipología de los equipamientos y servicios comerciales de las áreas turísticas de litoral. Esta relación permite identificar patrones espaciales a través de la delimitación de unidades territoriales con cierto grado de homogeneidad respecto a la oferta comercial. El resultado es la segmentación territorial de tales áreas, mediante la definición de zonas de preferencias, necesidades, motivaciones, comportamientos, hábitos, actitudes, expectativas y pautas de consumo de productos y servicios comerciales similares. El objetivo de este trabajo es analizar las pot…
An application of neural networks to natural scene segmentation
2006
This paper introduces a method for low level image segmentation. Pixels of the image are classified corresponding to their chromatic features.
Mean sets for building 3D probabilistic liver atlas from perfusion MR images
2012
This paper is concerned with liver atlas construction. One of the most important issues in the framework of computational abdominal anatomy is to define an atlas that provides a priori information for common medical task such as registration and segmentation. Unlike other approaches already proposed so far (to our knowledge), in this paper we propose to use the concept of random compact mean set to build probabilistic liver atlases. To accomplish this task a two-tier process was carried out. First a set of 3D images was manually segmented by a physician. We see the different 3D segmented shapes as a realization of a random compact set. Secondly, elements of two known definitions of mean set…
Analysis of normal human retinal vascular network architecture using multifractal geometry
2017
AIM To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyse…
A non-parametric Scale-based Corner Detector
2008
This paper introduces a new Harris-affine corner detector algorithm, that does not need parameters to locate corners in images, given an observation scale. Standard detectors require to fine tune the values of parameters which strictly depend on the particular input image. A quantitative comparison between our implementation and a standard Harris-affine implementation provides good results, showing that the proposed methodology is robust and accurate. The benchmark consists of public images used in literature for feature detection.
Object-based image analysis technique for gully mapping using topographic data at very high resolution (VHR)
2018
An accurate mapping of gullies is important since they are still major contributors of sediment to streams. Mapping gullies can be difficult because of the presence of dense canopy, which precludes the identification through aerial photogrammetry and other traditional remote sensing methods. Moreover, the wide spatial extent of some gullies makes their identification and characterization through field surveys a very large and expensive proposition. One cheaper and more expeditious way to detect gullies can be achieved in terms of morphological characteristics by the Digital Elevation Models (DEMs). The recent widespread availability of very high resolution (VHR) imagery, such as LIDAR data,…