Segmentação fuzzy de imagens e vídeos

Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented

Estudo do potencial da técnica de nanossísmica para o monitoramento de hidrofraturamento em reservatórios de hidrocarbonetos

Hydraulic fracturing is an operation in which pressurised fluid is injected in the geological formation surrounding the producing well to create new permeable paths for hydrocarbons. The injection of such fluids in the reservoir induces seismic events. The measurement of this reservoir stimulation can be made by location these induced microseismic events. However, microseismic monitoring is an expensive operation because the acquisition and data interpretation system using in this monitoring rely on high signal-to-noise ratios (SNR). In general, the sensors are deployed in a monitoring well near the treated well and can make a microseismic monitoring quite an expensive operation. In this dissertation we propose the application of a new method for recording and location of microseismic events called nanoseismic monitoring (Joswig, 2006). In this new method, a continuous recording is performed and the interpreter can separate events from noise using sonograms. This new method also allows the location of seismic sources even when P and S phases onsets are not clear like in situations of 0 dB SNR. The clear technical advantage of this new method is also economically advantageous since the sensors can potentially be installed on the surface rather than in observation well. In this dissertation field tests with controlled sources were made. In the first test small explosives using fire works at 28 m (slant distances) were detected yealding magnitudes between -2.4 ≤ ML ≤ -1.6.. In a second test, we monitored perforation shots in a producing oil field. In this second test, one perforation shot was located with slant distances of 861 m and magnitude 2.4 ML. Data from the tests allow us to say that the method has potential to be used in the oil industry to monitor hydrofracture