A Grey Level Fitting Mechanism based on Gompertz Function for Two Phase Flow Imaging using Electrical Capacitance Tomography Measurement Systems

Nombo, Josiah; Mwambela, Alfred; Kisangiri, Michael

doi:10.5120/17705-8704

Cited by 7 publications

(7 citation statements)

References 25 publications

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“…Three indicators were used to compare the three EIT, UST and EIT-UST tomographic methods: distribution error (DE), image correlation coefficient (ICC), and relative image error (RIE) [49]. The method of calculating DE is similar to MSE, but when comparing regression images, it takes the following form:…”

Section: Comparative Assessment Of Methods and Algorithmsmentioning

confidence: 99%

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Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

Kłosowski

Rymarczyk

Cieplak

et al. 2020

Sensors

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The paper presents the results of research on the hybrid industrial tomograph electrical impedance tomography (EIT) and ultrasonic tomography (UST) (EIT-UST), operating on the basis of electrical and ultrasonic data. The emphasis of the research was placed on the algorithmic domain. However, it should be emphasized that all hardware components of the hybrid tomograph, including electronics, sensors and transducers, have been designed and mostly made in the Netrix S.A. laboratory. The test object was a tank filled with water with several dozen percent concentration. As part of the study, the original multiple neural networks system was trained, the characteristic feature of which is the generation of each of the individual pixels of the tomographic image, using an independent artificial neural network (ANN), with the input vector for all ANNs being the same. Despite the same measurement vector, each of the ANNs generates its own independent output value for a given tomogram pixel, because, during training, the networks get their respective weights and biases. During the tests, the results of three tomographic methods were compared: EIT, UST and EIT-UST hybrid. The results confirm that the use of heterogeneous tomographic systems (hybrids) increases the reliability of reconstruction in various measuring cases, which is used to solve quality problems in managing production processes.

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Section: Comparative Assessment Of Methods and Algorithmsmentioning

confidence: 99%

Section: Comparative Assessment Of Methods and Algorithmsmentioning

confidence: 99%

Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

Kłosowski

Rymarczyk

Cieplak

et al. 2020

Sensors

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show abstract

“…In ECT grey level fitting using Gompertz function was proposed by [22]. The proposed model for image reconstruction unit using gompertz function grey level fitting consist of three main parts which include reconstruction stage, data fitting stage and display stage is as shown in Fig.…”

Section: Grey Level Fitting Based On Gompertz Fitting Functionmentioning

confidence: 99%

“…Parameters θ 1 and θ 2 in (12) are calculated Least Square method(LSM) [21,23,24]. The detailed procedure for calculating (θ 1 , θ 2 ) can be found in [22]. In the display stage the fitted grey levels are drawn and displayed as images.…”

Section: Fig 2 Ect Image Reconstruction Stage Incorporating Gompertmentioning

confidence: 99%

Performance Analysis of Grey Level Fitting Mechanism based Gompertz Function for Image Reconstruction Algorithms in Electrical Capacitance Tomography Measurement System

Nombo¹,

Mwambela²,

Kisangiri³

2015

IJCA

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This paper analyses the performance of grey level fitting mechanism based on Gompertz function used in Electrical Capacitance Tomography measurement system. In order to evaluate its performance, the data fitting mechanism has been applied to common image reconstruction algorithms which include; Linear Back Projection, Singular Value Decomposition, Tikhonov Regularization, Iterative Tikhonov Regularization, Landweber iteration and Projected Landweber iteration. Images were reconstructed using measured capacitance data for annular and stratified flows, and qualitative and quantitative evaluation were done on the reconstructed images in comparison with respective reference images. Results show that this grey level fitting mechanism is better in terms of improving image spatial resolution, minimizing relative image error and distribution error and maximizing correlation coefficient.

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“…Some reconstructions algorithms have been proposed to address the problem [16][17][18][19][20][21][22][23][24]. Others have improved images from LBP by further preprocessing the images using different approaches such as filtering [25], segmentation [26] and curve fitting [27].…”

Section: Introductionmentioning

confidence: 99%

Comparative Performance Evaluation of Entropic Thresholding Algorithms Based on Shannon, Renyi and Tsallis Entropy Definitions for Electrical Capacitance Tomography Measurement Systems

Mwambela¹

2018

IJISA

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Abstract-The concept of entropy as a measure of information has been extensively applied in information theory and related fields. The complex nature of information has resulted in some proposed entropy definitions. In image processing, the entropy concept has been used in developing thresholding techniques based on maximum entropy principles for image segmentation, enhancement and object detection purposes. In this article, entropy definitions are analysed to establish their relationship and after that evaluate their performance in image thresholding. Static simulated data from Electrical Capacitance Tomography measurement system for annular and stratified flows in multiphase hydrocarbons production has been used. Performance evaluation results of thresholding algorithms using Renyi entropy has shown to improve the measurements, particularly for stratified flow regimes. The improvement is solely based on the entropy definition, and it has been observed the introduced controlling parameters do not affect its performance. Renyi entropic thresholding algorithm is relatively robust as it is independent of the controlling parameter q and the grey level resolution. Therefore, there is the potential possibility of using Renyi entropic thresholding to improve measurements in hydrocarbons flow measurement using Electrical Capacitance Tomography measurement system.

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A Grey Level Fitting Mechanism based on Gompertz Function for Two Phase Flow Imaging using Electrical Capacitance Tomography Measurement Systems

Cited by 7 publications

References 25 publications

Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

Performance Analysis of Grey Level Fitting Mechanism based Gompertz Function for Image Reconstruction Algorithms in Electrical Capacitance Tomography Measurement System

Comparative Performance Evaluation of Entropic Thresholding Algorithms Based on Shannon, Renyi and Tsallis Entropy Definitions for Electrical Capacitance Tomography Measurement Systems

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