5 resultados para PALAEARCTIC REGION
em Universitat de Girona, Spain
Resumo:
Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach
A new approach to segmentation based on fusing circumscribed contours, region growing and clustering
Resumo:
One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed
Resumo:
In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method
Resumo:
In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach
Resumo:
The research we present here forms part of a two-phase project - one quantitative and the other qualitative - assessing the use of primary health care services. This paper presents the qualitative phase of said research, which is aimed at ascertaining the needs, beliefs, barriers to access and health practices of the immigrant population in comparison with the native population, as well as the perceptions of healthcare professionals. Moroccan and sub-Saharan were the immigrants to who the qualitative phase was specifically addressed. The aims of this paper are as follows: to analyse any possible implications of family organisation in the health practices of the immigrant population; to ascertain social practices relating to illness; to understand the significances of sexual and reproductive health practices; and to ascertain the ideas and perceptions of immigrants, local people and professionals regarding health and the health system. Methods: qualitative research based on discursive analysis. Data gathering techniques consisted of discussion groups with health system users and semi-structured individual interviews with healthcare professionals. The sample was taken from the Basic Healthcare Areas of Salt and Banyoles (belonging to the Girona Healthcare Region), the discussion groups being comprised of (a) 6 immigrant Moroccan women, (b) 7 immigrant sub-Saharan African women and (c) 6 immigrant and native population men (2 native men, 2 Moroccan men and 2 sub-Saharan men); and the semi-structured interviews being conducted with the following healthcare professionals: (a) 3 gynaecologists, (b) 3 nurses and 1 administrative staff. Results: use of the healthcare system is linked to the perception of not being well, knowledge of the healthcare system, length of time resident in Spain and interiorization of traditional Western medicine as a cure mechanism. The divergences found among the groups of immigrants, local people and healthcare professionals with regard to healthcare education, use of the healthcare service, sexual and reproductive healthcare and reticence with regard to being attended by healthcare personnel of the opposite sex demonstrate a need to work with the immigrant population as a heterogeneous group. Conclusions: the results we have obtained support the idea that feeling unwell is a psycho-social process, as it takes place within a specific socio-cultural situation and spans a range of beliefs, perceptions and ideas regarding symptomology and how to treat it