New Shadow Tracking method – for particle characterization
Shadow Tracking is a new method for particle characterization based on shadow measurements. Thanks to the implementation of the state of art edge detection algorithm, the accuracy of particle detection and particle segmentation are profoundly improved, even under non-ideal illumination conditions. Only a few parameters are needed for Shadow Tracking due to the analysis robustness. Moreover, Shadow Tracking can also identify overlapped particles to further improve the measurement accuracy. Shadow Tracking can generate a full description of particle characteristics, like geometric dimension, shape, position as well as velocity.
Shadow Tracking: Overlapped particles are rejected thereby improving measurement accuracy
New Phase Boundary Detection method – for dynamic masking i.a.
Accuracy of PIV measurements in two-phase flows is often reduced along the phase boundaries, due to the fact that the information from both phases are included in interrogation windows along the phase boundaries. Information along the phase boundary differs in terms of seeding density, velocity magnitude and flow direction across the boundary. Phase separated PIV measurements often minimize this problem and increase accuracy along the boundary by considering each phase separately.
The phase boundary detection module takes an image or double-framed image dataset and determines the phase boundaries in two-phase flows (flame fronts for combustion data or mixing of two liquids etc.). The method uses a combination of global thresholding and local thresholding to determine the phase boundaries. The gradient can also be used to subsequently filter away boundaries without a sharp gradient, which is mostly useful in flame front investigations in combustion diagnostics. The method can be used for dynamic masking, interface detection and application of certain filters on the detected interface.
Phase Boundary Detection: For dynamic masking, interface detection and more
New Merge 2D3C vectors to 3D3C vectors – for volumetric representation of scanning stereo PIV data
Many users performing volumetric PIV measurements are often challenged by a limited budget and lack of expertise. In this case, a cost efficient and suitable approach is the use of a Stereo PIV measurement setup that can be traversed within the volume of interest (see figure). On one hand, the user can resort to the more accustomed Stereo PIV measurements, on the other hand, it eliminates the need of additional cameras and the user is not restricted with smaller illuminated volumes or the necessity of using a high power laser to illuminate a larger volume as in the case of volumetric measurements. The new feature “Merge 2D vectors to 3D vectors” supports representing 2D vectors measured by a scanning stereo PIV setup as 3D vectors.
Stereo PIV measurement setup (2D) used to obtain a volumetric representation (3D) of data
New customizable Filter Library – for custom filters
Another new feature in DynamicStudio 5.1 is the addition of a customizable Filter Library in the Image Processing Library (IPL). Here users can save filter of their own choice and design or make use of the predefined filters. Square and odd-sized kernels from 3×3 to 15×15 are supported and filter coefficients can be either floating point or integer values. In the former case, processed images will also be floating point, while the latter will produce images with the same gray-scale depth as the parent image. For integer image formats grayscale values will be truncated at zero and at the upper limit (e.g. 255, 1023 or 4095 for 8-, 10- or 12-bit images, respectively). To avoid or reduce overflow, a filter divisor can be specified when integer filter values have chosen.
A customized filter in the new Filter Library – here 11×11 Gaussian filter