A concurrent region growing algorithm guided by circumscribed contours

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

Implementació d’un sistema xat multiprotocol fent servir el llenguatge de programació ERLANG

Construcció d’una aplicació amb un llenguatge de programació concurrent i distribuït anomenat Erlang. Erlang és un llenguatge de programació funcional amb avaluació estricta, és a dir, assignació única i que inclou una màquina virtual. L’aplicació desenvolupada ha estat la programació d’un xat multiprotocol, el qual s’ha realitzat una primera part que ha consistit en el construcció d’un servidor per la xarxa local i el seu corresponent client. Llavors per poder fer un client més funcional i útil s’ha implementat un altre protocol, IRC. Al tractar-se d’un llenguatge espacialment dissenyat per treballar en processos s’ha intentat dissenyar d’una manera la qual es pugés aprofitar aquesta qualitat

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

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

Efficiency and Equity in Learning Communities and schools

Traditionally, school efficiency has been measured as a function of educational production. In the last two decades, however, studies in the economics of education have indicated that more is required to improve school efficiency: researchers must explore how significant changes in school organization affect the performance of at-risk students. In this paper we introduce Henry Levin’s adoption of the X-efficiency approach to education and we describe the efficient and cost-effective characteristics of one Learning Communities Project School that significantly improved its student outcomes and enrollment numbers and reduced its absenteeism rate to zero. The organizational change that facilitated these improvements defined specific issues to address. Students’ school success became the focus of the school project, which also offered specific incentives, selected teachers, involved parents and community members in decisions, and used the most efficient technologies and methods. This case analysis reveals new two elements—family training and community involvement—that were not explicit parts of Levin’s adaptation. The case of the Antonio Machado Public School should attract the attention of both social scientists and policy makers

Estudio del impacto ambiental del uso del bagazo como fuente de energía en centrales azucareros en Cuba. Estudio de caso "Melanio Hernández"

This work was carried out to study the environmental impacts produced by power generation from biomass (bagasse) in sugar mills in Cuba. For this purpose, with the collaboration of the Center for Energy and Industrial Processes (CEEPI), the University Center of Sancti Spiritus and using different research methods and techniques, conducted an environmental survey of the area. Gaseous emissions were characterized and the suspended solid particles, allowing knowing that these concentrations do not exceed the maximum emission limit set by the cubana Standard. In addition, the dispersion model applied DISPER allowed us to obtain information in crisis conditions of air emissions from sugar mill and distillery associated and concluded that emissions from the distillery are the pollutants that contribute more the atmosphere. The correlating emissions with respiratory diseases, (acute respiratory infections or subacute (IRA) and ASMA), concurrent Asthma Crisis (CAB) is the most affected. The calculated costs associated in these diseases, amounting to $ 119 599.23 per year. In order to minimize the negative alternatives are proposed to be implemented in industry and community.

A proposal to estimate the motion of an underwater vehicle through visual mosaicking

This thesis proposes a solution to the problem of estimating the motion of an Unmanned Underwater Vehicle (UUV). Our approach is based on the integration of the incremental measurements which are provided by a vision system. When the vehicle is close to the underwater terrain, it constructs a visual map (so called "mosaic") of the area where the mission takes place while, at the same time, it localizes itself on this map, following the Concurrent Mapping and Localization strategy. The proposed methodology to achieve this goal is based on a feature-based mosaicking algorithm. A down-looking camera is attached to the underwater vehicle. As the vehicle moves, a sequence of images of the sea-floor is acquired by the camera. For every image of the sequence, a set of characteristic features is detected by means of a corner detector. Then, their correspondences are found in the next image of the sequence. Solving the correspondence problem in an accurate and reliable way is a difficult task in computer vision. We consider different alternatives to solve this problem by introducing a detailed analysis of the textural characteristics of the image. This is done in two phases: first comparing different texture operators individually, and next selecting those that best characterize the point/matching pair and using them together to obtain a more robust characterization. Various alternatives are also studied to merge the information provided by the individual texture operators. Finally, the best approach in terms of robustness and efficiency is proposed. After the correspondences have been solved, for every pair of consecutive images we obtain a list of image features in the first image and their matchings in the next frame. Our aim is now to recover the apparent motion of the camera from these features. Although an accurate texture analysis is devoted to the matching pro-cedure, some false matches (known as outliers) could still appear among the right correspon-dences. For this reason, a robust estimation technique is used to estimate the planar transformation (homography) which explains the dominant motion of the image. Next, this homography is used to warp the processed image to the common mosaic frame, constructing a composite image formed by every frame of the sequence. With the aim of estimating the position of the vehicle as the mosaic is being constructed, the 3D motion of the vehicle can be computed from the measurements obtained by a sonar altimeter and the incremental motion computed from the homography. Unfortunately, as the mosaic increases in size, image local alignment errors increase the inaccuracies associated to the position of the vehicle. Occasionally, the trajectory described by the vehicle may cross over itself. In this situation new information is available, and the system can readjust the position estimates. Our proposal consists not only in localizing the vehicle, but also in readjusting the trajectory described by the vehicle when crossover information is obtained. This is achieved by implementing an Augmented State Kalman Filter (ASKF). Kalman filtering appears as an adequate framework to deal with position estimates and their associated covariances. Finally, some experimental results are shown. A laboratory setup has been used to analyze and evaluate the accuracy of the mosaicking system. This setup enables a quantitative measurement of the accumulated errors of the mosaics created in the lab. Then, the results obtained from real sea trials using the URIS underwater vehicle are shown.