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Accurate and efficient measurement of fluid velocities in several kind of experiments, has been acquiring high relevance, for several kind of applications. Particle Image Velocimetry is a noninvasive technique which also provides velocity estimates in several points of the measuring region. Regarding the PIV computations, high resolution of the digital input images, may lead to poor performance. There are also many error sources, regarding the PIV setup itself. This paper describes a method aimed both to speeding up the PIV computations, and minimizing the divergences (noise) present in the output velocity fields. The obtained results are promising, obtaining a speedup of up to 55 % , with respect to the traditional cross correlation based method, with a comparable precision.

The lack of hydrological data has been identified as one of the major obstacles facing the effective evaluation of hydraulic and hydrological interventions in the field. Traditional methods of data collection have proven to be generally expensive and particularly risky under high flow conditions. A method for quantifying hydrodynamic variables, such as surface flow velocity and discharge volume was developed in a laboratory setting using video images. This method explores several innovative image analysis techniques, specifically the Image Variance (IV) and Threshold Segmentation with Path Discretization (TSPD), where the basics steps comprise image capture, rectification and data extraction. Measurements obtained from conventional instruments and data extracted from video images were compared and exhibited less than 2.5% difference. It can be concluded that under laboratory conditions it is possible to obtain reliable velocities and discharges from video techniques, without being in contact with the flow.