We demonstrate the viability of using four low-cost smartphone cameras to perform Tomographic PIV. We use colored shadows to imprint two or three different time-steps on the same image. The back-lighting is accomplished with three sets of differently-colored pulsed LEDs. Each set of Red, Green & Blue LEDs is shone on a diffuser screen facing each of the cameras. We thereby record the RGB-colored shadows of opaque suspended particles, rather than the conventionally used scattered light. We subsequently separate the RGB color channels, to represent the separate times, with preprocessing to minimize noise and cross-talk. We use commercially available Tomo-PIV software for the calibration, 3-D particle reconstruction and particle-field correlations, to obtain all three velocity components in a volume. Acceleration estimations can be done thanks to the triple pulse illumination. Our test flow is a vortex ring produced by forcing flow through a circular orifice, using a flexible membrane, which is driven by a pressurized air pulse. Our system is compared to a commercial stereoscopic PIV system for error estimations. We believe this proof of concept experiment will make this technique available for education, industry and scientists for a fraction of the hardware cost needed for traditional Tomo-PIV.
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http://dx.doi.org/10.1038/s41598-017-03722-9 | DOI Listing |
Heliyon
November 2024
Institute of Cultural Heritage, Shandong University, Qingdao, 266237, China.
Biodivers Data J
November 2024
CIBIO Centro de Investigación em Biodiversidade e Recursos Genéticos, Porto, Portugal CIBIO Centro de Investigación em Biodiversidade e Recursos Genéticos Porto Portugal.
Variations in colouration patterns have been reported in numerous wildlife species, particularly birds. However, the increased use of camera traps for wildlife monitoring has enabled the detection of elusive species and phenotypic variations that might otherwise go undetected. Here, we compiled records of unusual colouration patterns in terrestrial mammals, documented through camera-trap studies over a 12-year period in the Llanganates-Sangay Connectivity Corridor, in the Tropical Andes of Ecuador.
View Article and Find Full Text PDFSci Rep
November 2024
College of Computer Science and Technology, Hengyang Normal University, Hengyang, China.
Architectural photography style transfer, a task in computer vision, employs deep learning algorithms to transform the style of architectural photograph while preserving key structure and content. Existing algorithms face challenges due to the intricate details of buildings, including diverse shapes, lines, and textures. Moreover, considerations for artistic effects in architectural photography style transfer, such as lighting, shadows, and atmosphere, require high-quality image generation algorithms.
View Article and Find Full Text PDFMar Pollut Bull
January 2025
School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China.
Harmful algal blooms (HABs) pose serious threats to coastal economies and ecosystems, yet effective monitoring remains challenging due to diverse bloom types and complex environmental conditions. This paper proposes a Mixed Algal Blooms Index (MABI) that uses a new color space to improve HABs detection. By employing Sentinel-2's near-infrared, short-wave infrared, and green bands to calculate tristimulus values-replacing traditional RGB bands-MABI significantly enhances the distinction between algal blooms and water.
View Article and Find Full Text PDFEnviron Res
January 2025
Key Laboratory of Marine Ecological Conservation and Restoration, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China. Electronic address:
The pollution of micro- and mesoplastic (MMP) in the Eastern Indian Ocean (EIO) remains poorly understood. The present study revealed that MMP abundance in nekton from EIO in 2022 (mean: 2.30 ± 0.
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