Indústria

This paper proposes an algorithm to detect oil spills in Synthetic Aperture Radar (SAR) images that can be used to support environmental remote monitoring. The proposed algorithm combines the region growing approach and the multiresolution analysis employed by the undecimated wavelet transform to localize dark areas in the sea. The undecimated wavelet applied to the test image smooths the speckle noise while enhances edges providing a better result of the proposed segmentation algorithm that is achieved by a modified region growing approach.

This paper presents a simulator to help electrical engineering students and professionals in the learning process. The proposed tool embodies Virtual Reality technologies on the improvement of understanding equipment maneuvers in distribution power systems. The tool has a virtual didactic distribution network in which the students handle several real tasks related to operation and maintenance of distribution network through applied technology. We hope that this tool can contribute to develop and improve professional skills in engineering at a low cost and furthermore it supports laboratory and associated technical activities.

The paper proposes an algorithm to segment spots in synthetic aperture radar (SAR) images in order to support environmental remote monitoring. This approach consists of isolating dark areas that may have originated from oil pollution, thus achieving the aim of our investigation. The proposed algorithm combines a region growing approach and a multiscale analysis employed by an undecimated wavelet transform

The paper proposes an algorithm to segment spots in synthetic aperture radar (SAR) images in order to support environmental remote monitoring. This approach consists of isolating dark areas that may have originated from oil pollution, thus achieving the aim of our investigation. The proposed algorithm combines a region growing approach and a multiscale analysis employed by an undecimated wavelet transform