Towards Detecting Changes in Underwater Image Sequences

Detecting changes between images of the same scene taken at different times is of great interest for monitoring and understanding the environment. It is widely used for on-land application but suffers from different constraints. Unfortunately, Change detection algorithms require highly accurate geometric and photometric registration. This requirement has precluded their use in underwater imagery in the past. In this paper, the change detection techniques available nowadays for on-land application were analyzed and a method to automatically detect the changes in sequences of underwater images is proposed. Target application scenarios are habitat restoration sites, or area monitoring after sudden impacts from hurricanes or ship groundings. The method is based on the creation of a 3D terrain model from one image sequence over an area of interest. This model allows for synthesizing textured views that correspond to the same viewpoints of a second image sequence. The generated views are photometrically matched and corrected against the corresponding frames from the second sequence. Standard change detection techniques are then applied to find areas of difference. Additionally, the paper shows that it is possible to detect false positives, resulting from non-rigid objects, by applying the same change detection method to the first sequence exclusively. The developed method was able to correctly find the changes between two challenging sequences of images from a coral reef taken one year apart and acquired with two different cameras

La incontinencia urinaria en el cáncer de próstata: diseño de un programa de rehabilitación

Este trabajo presenta el diseño e implementación de un programa progresivo de rehabilitación basado en los ejercicios musculares del suelo pélvico, incorporando el trabajo muscular de fuerza contrarresistencia. El disenño del estudio es casi experimental.La muestra es de 33 participantes en fase de tratamiento. Las variables de estudio son las antropométricas, las relacionadas con la evolución de la incontinencia urinaria(IU (intensidad, dificultad, frecuencia y limitación de las actividades),la obesidad, fatiga y dolor,la fuerza muscular y la calidad de vida(CdV). Para evaluar el cambio intrasujeto se tomaron medidas pretest(semana 0)y postest(semana24. En el análisis estadístico se utilizan las pruebas t Student-Fisher, Wilcoxon oU de Mann Whitney y el test del w2. El análisis se realiza con el programa SPSS versión 15. El nivel de significación escogido es del 5%. Al finalizar las 24 semanas del programa se identifica una disminución significativa de las variables antropométricas índice de cintura cadera (p¼0,003), perímetro de cintura(pr0,001) y porcentaje de masa de grasa(pr0,001); de las variables de IU: intensidad(pr0,0001), frecuencia y dificultad y su relación con la limitación de las actividades (pr0,0001), así como la relación existente entre la mejora de IU y la mejora de la CdV(p¼0,039). Queda científicamente demostrada la eficacia del programa progresivo de fuerza para disminuir la IU. La mejora de la CdV del hombre mayor con cáncer de prósstata viene mediada por la mejora de la continencia urinaria

Application of discriminant function analysis and change-point problem in dating volcanic ashes

The application of Discriminant function analysis (DFA) is not a new idea in the study of tephrochrology. In this paper, DFA is applied to compositional datasets of two different types of tephras from Mountain Ruapehu in New Zealand and Mountain Rainier in USA. The canonical variables from the analysis are further investigated with a statistical methodology of change-point problems in order to gain a better understanding of the change in compositional pattern over time. Finally, a special case of segmented regression has been proposed to model both the time of change and the change in pattern. This model can be used to estimate the age for the unknown tephras using Bayesian statistical calibration

Detection of matchings in a sequence of underwater images through texture analysis

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability