bubble measurement
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2020 ◽  
Vol 97 ◽  
pp. 106771
Author(s):  
Gabriel Machado Lunardi ◽  
Guilherme Medeiros Machado ◽  
Vinicius Maran ◽  
José Palazzo M. de Oliveira

Author(s):  
Thomas Shepard ◽  
Thomas Höft

Abstract Accurate measurement of bubble size in digital images can prove challenging in conditions that involve significant overlapping of bubbles and/or images with a combination of in and out of focus bubbles. The method employed in the current study uses the circular Hough transform to identify circular features in the image. This method can handle mildly non-circular (i.e. non-spherical) bubbles as well as non-trivial overlapping. Several image pre-processing steps are employed to improve the method’s accuracy in detecting in-focus bubbles along with their radii, reduce both spurious detection of out-of-focus bubbles and non-bubble features, and reduce non-detection of in-focus bubbles. Pre-processing steps include histogram equalization and illumination variation reduction via filtering. In this paper, results from the algorithm are compared against a manual detection of bubbles in digital images under conditions of varying bubble diameter and bubble number density.


2018 ◽  
Vol 2018.93 (0) ◽  
pp. P056
Author(s):  
Atsuo KUBONISHI ◽  
Yohsuke TANAKA ◽  
Shigeru MURATA

Author(s):  
C. Zelenka ◽  
R. Koch

Marine gas seeps, such as in the Panarea area near Sicily (McGinnis et al., 2011), emit large amounts of methane and carbon-dioxide, greenhouse gases. Better understanding their impact on the climate and the marine environment requires precise measurements of the gas flux. Camera based bubble measurement systems suffer from defocus blur caused by a combination of small depth of field, insufficient lighting and from motion blur due to rapid bubble movement. These adverse conditions are typical for open sea underwater bubble images. As a consequence so called ’bubble boxes’ have been built, which use elaborate setups, specialized cameras and high power illumination. A typical value of light power used is 1000W (Leifer et al., 2003). <br><br> In this paper we propose the compensation of defocus and motion blur in underwater images by using blind deconvolution techniques. The quality of the images can be greatly improved, which will relax requirements on bubble boxes, reduce their energy consumption and widen their usability.


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