Image Fusion Using Fuzzy Logic Pixel Fusion for Dual Modality Tomography System

Pusppanathan, Jaysuman; Faramarzi, Mahdi; Yunus, Fazlul Rahman Mohd; Ayob, Nor Muzakkir Nor; Rahim, Ruzairi Abdul; Phang, Fatin Aliah; Rahiman, Mohd Hafiz Fazalul; Ahmad, Anita; Ling, Leow Pei; Abas, Khairul Hamimah

doi:10.11113/jt.v70.3460

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…Although the algorithm employed in the approach is a pixel-by-pixel determination of phase concentration, it is not difficult to adapt other algorithms, e.g. fuzzy logic [23] to improve the results.…”

Section: Discussionmentioning

confidence: 99%

“…Image-based fusion is the most widely applied approach for DMTS, due to the computational and implementational simplicity. In this case, reconstructed data can be fused simply using thresholding [6], [8], [11], [16], [18], [22], or employing advanced algorithms, such as fuzzy logic [23] or fuzzy c-means (FCM) [17].…”

Section: Introductionmentioning

confidence: 99%

“…The majority of them took account of the fusion at spatial and frequency level, but excluding temporal data, [6], [16], [17], and hence were only able to reveal limited information regarding flow regimes. Although others integrated aforementioned multi-dimensional contents [11], [23], their applicabilities were still restricted to slug flow and annular flow. To our best knowledge, no existing method has been evaluated by real-world industrial cases.…”

Section: Introductionmentioning

confidence: 99%

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Visualization of Gas–Oil–Water Flow in Horizontal Pipeline Using Dual-Modality Electrical Tomographic Systems

Wang

Wei

et al. 2017

IEEE Sensors J.

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Employing dual-modality tomography inherently involves data from multiple dimensions, and thus a coherent approach is required to fully exploit the information from various dimensions. This paper describes a novel approach for dualmodality electrical resistance and capacitance tomography (ERT-ECT) to visualize gas-oil-water flow in horizontal pipeline. Compared to conventional methods with dual-modality tomographic systems, the approach based on thresholding takes account of multi-dimensional data, which therefore is capable of providing insights into investigated flow in both spatial and temporal terms. The experimental results demonstrate the feasibility of the approach, by which 6 common flow regimes in horizontal pipeline flow are visualized based on the multi-dimensional data with ERT-ECT systems, including (wavy) stratified flow, plug flow, slug flow, annular flow and bubbly flow. Although the present approach is proposed for data acquired with ERT-ECT system, it is potentially adaptable to other dual-modality tomographic systems that use concentration tomograms as inputs.Index Terms-Dual-modality electrical tomography, multiphase flow measurement and visualization, multi-dimensional data fusion, flow regimes visualization.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Visualization of Gas–Oil–Water Flow in Horizontal Pipeline Using Dual-Modality Electrical Tomographic Systems

Wang

Wei

et al. 2017

IEEE Sensors J.

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“…However, whether their approach is applicable to three-phase flow remains a question since there is a fundamental difference between two-phase flow and three-phase due to the introduction of an extra phase. Pusppanathan et al [21] proposed fuzzy logic for ultrasonic tomography (UT) and ECT to integrate separately reconstructed images. The proposed method, however, was still at the stage of proof of concept and only evaluated at spatial dimension with simulated data.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based Multi-Dimensional Image Fusion for Gas–Oil-Water Flows With Dual-Modality Electrical Tomography

Wang

Jia

Wang

2020

IEEE Trans. Instrum. Meas.

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This paper proposes a novel approach whereby fuzzy logic and decision tree are utilised to overcome the challenges in analysing images of gas-oil-water pipeline flow obtained using electrical resistance and capacitance dual-modality tomography. The approach firstly generates two axially-stacked concentration images from two stacks of the cross-sectional concentration tomograms reconstructed from different modalities respectively, and then registers two generated images in temporal and spatial terms. Afterwards, a fuzzy logic method is applied to perform a pixel-level fusion to integrate the registered images based on the characteristics of electrical tomograms for multiphase pipeline flow. Later, a decision tree is utilised to derive the local concentration of each individual phase according to the fusion results. Using the data from real industrial cases, both feasibility and robustness of the proposed approach are demonstrated. In addition, the proposed approach also overcomes the limitations of conventional threshold-based methods on the request of priori knowledge for the qualitative and quantitative analyses of gas-oil-water pipeline flow.

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Image Fusion Using Fuzzy Logic Pixel Fusion for Dual Modality Tomography System

Cited by 2 publications

References 8 publications

Visualization of Gas–Oil–Water Flow in Horizontal Pipeline Using Dual-Modality Electrical Tomographic Systems

Visualization of Gas–Oil–Water Flow in Horizontal Pipeline Using Dual-Modality Electrical Tomographic Systems

Fuzzy Logic Based Multi-Dimensional Image Fusion for Gas–Oil-Water Flows With Dual-Modality Electrical Tomography

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