A method for recognizing overlapping elliptical bubbles in bubble image

Zhang, Wenhui; Jiang, Xiaosong; Liu, Yin-Mingzi

doi:10.1016/j.patrec.2012.03.027

Cited by 101 publications

(69 citation statements)

References 31 publications

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“…Photography is the simplest and the most direct method that has been widely used due to the advantage of simple operation. However, bubbles overlapping 23 is a common problem for high gas holdup situations. Microphotography 24 is a technology combining camera with microscope.…”

Section: Methodsmentioning

confidence: 99%

Gas‐Liquid Mass Transfer Characteristics with Microbubble Aeration – I. Standard Stirred Tank

Zu³

et al. 2016

Chem Eng & Technol

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More knowledge has to be acquired on the gas-liquid mass transfer characteristics with microbubble aeration before an efficient bioreactor is designed. Experiments about this subject have been conducted in a stirred reactor. Some valuable conclusions were obtained: the shaft power consumption is little affected by the superficial gas velocity (v s ) and the power consumption of the microbubble generator is rather high; the dispersion of microbubbles is more uniform compared to sparger aeration; surface aeration leads to a reduced microbubble number and the diameter of the microbubble increases with higher superficial gas velocity; when surface aeration happens, the k L a-v s curves turn quite abnormally different from that in the case of sparger aeration, and correlation-based calculations fit well with the measurements.

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Section: Methodsmentioning

confidence: 99%

Gas‐Liquid Mass Transfer Characteristics with Microbubble Aeration – I. Standard Stirred Tank

Zu³

et al. 2016

Chem Eng & Technol

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“…It however fails to converge when large number of closely spaced overlapped objects are present in the image. In (Zhang et al, 2012), the problem of segmenting overlapping elliptical bubbles is solved by segmenting the extracted contours into curves. These curves are further segmented into groups belonging to the same bubble followed by ellipse fitting.…”

Section: Related Workmentioning

confidence: 99%

Image Segmentation of Multi-shaped Overlapping Objects

Kumar

Chauhan

Sarkar

2018

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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In this work, we propose a new segmentation algorithm for images containing convex objects present in multiple shapes with a high degree of overlap. The proposed algorithm is carried out in two steps, first we identify the visible contours, segment them using concave points and finally group the segments belonging to the same object. The next step is to assign a shape identity to these grouped contour segments. For images containing objects in multiple shapes we begin first by identifying shape classes of the contours followed by assigning a shape entity to these classes. We provide a comprehensive experimentation of our algorithm on two crystal image datasets. One dataset comprises of images containing objects in multiple shapes overlapping each other and the other dataset contains standard images with objects present in a single shape. We test our algorithm against two baselines, with our proposed algorithm outperforming both the baselines.

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“…In [35], the segmentation of overlapping bubbles was approached using concave points extraction through the polygonal approximation and ellipse fitting. The method was, however, developed for practically noise-free images where bubbles were clearly distinguishable from the background.…”

Section: Other Approachesmentioning

confidence: 99%

Detection of bubbles as concentric circular arrangements

Strokina

Matas

Eerola

et al. 2016

Machine Vision and Applications

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The paper proposes a method for the detection of bubble-like transparent objects in a liquid. The detection problem is non-trivial since bubble appearance varies considerably due to different lighting conditions causing contrast reversal and multiple interreflections. We formulate the problem as the detection of concentric circular arrangements (CCA). The CCAs are recovered in a hypothesize-optimizeverify framework. The hypothesis generation is based on sampling from the partially linked components of the nonmaximum suppressed responses of oriented ridge filters, and is followed by the CCA parameter estimation. Parameter optimization is carried out by minimizing a novel cost-function. The performance was tested on gas dispersion images of pulp suspension and oil dispersion images. The mean error of gas/oil volume estimation was used as a performance criterion due to the fact that the main goal of the applications driving the research was the bubble volume estimation. The method achieved 28 and 13 % of gas and oil volume estimation errors correspondingly outperforming the OpenCV Circular Hough Transform in both cases and the WaldBoost detector in gas volume estimation.B Tuomas Eerola tuomas.eerola@lut.fi

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A method for recognizing overlapping elliptical bubbles in bubble image

Cited by 101 publications

References 31 publications

Gas‐Liquid Mass Transfer Characteristics with Microbubble Aeration – I. Standard Stirred Tank

Gas‐Liquid Mass Transfer Characteristics with Microbubble Aeration – I. Standard Stirred Tank

Image Segmentation of Multi-shaped Overlapping Objects

Detection of bubbles as concentric circular arrangements

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