Image-Based Technique for Turbulent Flow Segmentation

Osman, A.B. and Ovinis, M. and Faye, I. and Hashim, F.M. (2018) Image-Based Technique for Turbulent Flow Segmentation. Lecture Notes in Electrical Engineering, 488. pp. 119-129.

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Abstract

Turbulent flow segmentation from image data is a challenging problem. This is due to the un-defined edge and the complex flow nature of turbulence. In this paper, an image-based technique is proposed for turbulent flow segmentation from image. The proposed technique segments the flow region based on enhancing the input image intensity at flow edges and by defining a thresholding value to differentiate between flow region and image background. To test the image-based segmentation technique, a turbulent buoyant jet was experimentally simulated at different nozzle flow rates which have a Reynolds numbers of 960, 1560, and 3210. Then, a video camera was used to record the jet flow data. Then, the image-based technique was applied to segment the flow region and estimate the jet penetration area. As a result, the turbulent flow region was segmented well for all cases of nozzle flow rates. Moreover, application of the image-based technique for jet penetration estimation showed a good agreement with the previous work, in which the jet propagated linearly over time. © 2018, Springer Nature Singapore Pte Ltd.

Item Type: Article
Impact Factor: cited By 0; Conference of 4th International Conference on Computational Science and Technology, ICCST17 ; Conference Date: 29 November 2017 Through 30 November 2017; Conference Code:211169
Uncontrolled Keywords: Image enhancement; Nozzles; Reynolds number; Turbulent flow; Video cameras, Buoyant jets; Complex flow; Flow regions; Image-based techniques; Jet penetration; Penetration area; Segmentation techniques; Turbulent jet, Image segmentation
Departments / MOR / COE: Research Institutes > Institute for Health Analytics
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 01 Aug 2018 01:12
Last Modified: 23 Oct 2018 01:36
URI: http://scholars.utp.edu.my/id/eprint/21923

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