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Article
Publication date: 19 September 2016

Ziqiang Cui, Qi Wang, Qian Xue, Wenru Fan, Lingling Zhang, Zhang Cao, Benyuan Sun, Huaxiang Wang and Wuqiang Yang

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low…

Abstract

Purpose

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

Design/methodology/approach

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

Findings

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

Originality/value

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

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Article
Publication date: 16 August 2019

Shuangshuang Liu and Xiaoling Li

Conventional image super-resolution reconstruction by the conventional deep learning architectures suffers from the problems of hard training and gradient disappearing. In…

Abstract

Purpose

Conventional image super-resolution reconstruction by the conventional deep learning architectures suffers from the problems of hard training and gradient disappearing. In order to solve such problems, the purpose of this paper is to propose a novel image super-resolution algorithm based on improved generative adversarial networks (GANs) with Wasserstein distance and gradient penalty.

Design/methodology/approach

The proposed algorithm first introduces the conventional GANs architecture, the Wasserstein distance and the gradient penalty for the task of image super-resolution reconstruction (SRWGANs-GP). In addition, a novel perceptual loss function is designed for the SRWGANs-GP to meet the task of image super-resolution reconstruction. The content loss is extracted from the deep model’s feature maps, and such features are introduced to calculate mean square error (MSE) for the loss calculation of generators.

Findings

To validate the effectiveness and feasibility of the proposed algorithm, a lot of compared experiments are applied on three common data sets, i.e. Set5, Set14 and BSD100. Experimental results have shown that the proposed SRWGANs-GP architecture has a stable error gradient and iteratively convergence. Compared with the baseline deep models, the proposed GANs models have a significant improvement on performance and efficiency for image super-resolution reconstruction. The MSE calculated by the deep model’s feature maps gives more advantages for constructing contour and texture.

Originality/value

Compared with the state-of-the-art algorithms, the proposed algorithm obtains a better performance on image super-resolution and better reconstruction results on contour and texture.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 15 May 2020

Rajkumar Gothandaraman and Sreekumar Muthuswamy

This paper aims to propose a system to acquire images automatically for digital reconstruction of heritage artifacts using a six-degree of freedom industrial manipulator.

Abstract

Purpose

This paper aims to propose a system to acquire images automatically for digital reconstruction of heritage artifacts using a six-degree of freedom industrial manipulator.

Design/methodology/approach

A virtual environment is created using Robot Studio® software to integrate the trajectory and differential motion of the robot manipulator and the motion of camera while acquiring images. A new area similarity matrix method is proposed to reduce the number of images required for digital reconstruction using Autodesk Recap® software. Real-time experiments have been performed using objects such as minion, ultimaker robot and cube. Evaluation of the digital reconstruction is conducted using the contour area matching method.

Findings

The number of images required for reconstruction based on area similarity matrix method is reduced to 63 per cent when compared with the random selection method. Quality parameters such as surface area, volume, number of defect holes, vertices and faces are enhanced for the proposed method.

Research limitations/implications

Digital reconstruction of large-sized heritage artifacts cannot be performed in this setup. But this can be overcome by fixing the manipulator on a mobile platform or overhead crane. This paper does not discuss the reconstruction of partially damaged heritage artifacts, which could be accomplished based on deep learning techniques.

Practical implications

Using this approach, off-the-shelf heritage artifacts and large-scale objects can be reconstructed digitally with a minimum number of images and without compromising the quality of original models.

Originality/value

To the best of the authors’ knowledge, area similarity-based approach in 3D digital reconstruction by coupling the kinematics of an industrial manipulator and camera is proposed for the first time. A fully automated digital reconstruction technology to preserve valuable heritage artifacts has been developed. It also highlights the space constraints of the industrial manipulator in digital reconstruction.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 19 June 2017

Qi Wang, Pengcheng Zhang, Jianming Wang, Qingliang Chen, Zhijie Lian, Xiuyan Li, Yukuan Sun, Xiaojie Duan, Ziqiang Cui, Benyuan Sun and Huaxiang Wang

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the…

Abstract

Purpose

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

Design/methodology/approach

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Findings

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

Originality/value

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Details

Sensor Review, vol. 37 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 4 April 2016

Anneke Soraya Hidayat, Gil-Je Lee, Eun-Jun Yoon and Kee-Young Yoo

The detection of an adversary in secret image sharing has been a problematic side in the reconstruction phase. Some of verifiable secret sharing solutions have been…

Abstract

Purpose

The detection of an adversary in secret image sharing has been a problematic side in the reconstruction phase. Some of verifiable secret sharing solutions have been proposed to solve the problem. However, there is some computational limitation in the previous schemes. The purpose of this paper is to analyze the importance of consistency for detecting an adversary in a secure reconstruction phase. Strong t-consistency assures the correctness of reconstructed secret as long as participants P ∈ N and n(P) = t. Consistency is a solution for preventing the participant to be absent and helps the dealer to easily detect the adversary without an additional verification step.

Design/methodology/approach

This paper focuses on secure reconstruction, and uses two different approaches, namely, single-secret and multi-secret, to experiment the relationship between the given variable (t,m,n) and the adversaries by observing the quality test result, polynomial approach and visualization.

Findings

The results show that t and m are inversely proportional to the image quality without respect to the polynomial approach. The reconstruction phase is declared as securely conducted when m = 2t − 1, for both single- and multi-secret approaches.

Originality/value

The application of consistency is a considerable step for securing the secret from an adversary by combining the reconstruction phase and the consistency combination at once, removing the need for additional separate verification steps for decreasing the computational time, especially in secret image sharing.

Details

International Journal of Pervasive Computing and Communications, vol. 12 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

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Article
Publication date: 31 December 2020

Tomasz Rymarczyk, Konrad Kania, Michał Gołąbek, Jan Sikora, Michał Maj and Przemysław Adamkiewicz

The purpose of this study is to develop a reconstruction and measurement system for data analysis using ultrasonic transmission tomography. The problem of reconstruction

Abstract

Purpose

The purpose of this study is to develop a reconstruction and measurement system for data analysis using ultrasonic transmission tomography. The problem of reconstruction from the projection is encountered in practical implementation, which consists in reconstructing an image that is an estimation of an unknown object from a finite set of projection data. Reconstructive algorithms used in transmission tomography are based on linear mathematical models, which makes it necessary to process non-linear data into estimates for a finite number of projections. The application of transformation methods requires building a mathematical model in which the projection data forming the known and unknown quantities are functions with arguments from a continuous set of real numbers, determining the function describing the unknown quantities sought in the form of inverse relation and adapting it to operate on discrete and noisy data. This was done by designing a tomographic device and proprietary algorithms capable of reconstructing two-dimensional images regardless of the size, shape, location or number of inclusions hidden in the examined object.

Design/methodology/approach

The application consists of a device and measuring sensors, as well as proprietary algorithms for image reconstruction. Ultrasonic transmission tomography makes it possible to analyse processes occurring in an object without interfering with the examined object. The proposed solution uses algorithms based on ray integration, the Fermat principle and deterministic methods. Two applications were developed, one based on C and implemented on the embedded device, while the other application was made in Matlab.

Findings

Research shows that ultrasonic transmission tomography provides an effective analysis of tested objects in closed tanks.

Research limitations/implications

In the presented technique, the use of ultrasonic absorption wave has been limited. Nevertheless, the effectiveness of such a solution has been confirmed.

Practical implications

The presented solution can be used for research and monitoring of technological processes.

Originality/value

Author’s tomographic system consisting of a measuring system and image reconstruction algorithms.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 40 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 19 January 2015

C.L. Yang, A. Mohammed, Y Mohamadou, T. I. Oh and M. Soleimani

The aim of this paper is to introduce and to evaluate the performance of a multiple frequency complex impedance reconstruction for fabric-based EIT pressure sensor…

Abstract

Purpose

The aim of this paper is to introduce and to evaluate the performance of a multiple frequency complex impedance reconstruction for fabric-based EIT pressure sensor. Pressure mapping is an important and challenging area of modern sensing technology. It has many applications in areas such as artificial skins in Robotics and pressure monitoring on soft tissue in biomechanics. Fabric-based sensors are being developed in conjunction with electrical impedance tomography (EIT) for pressure mapping imaging. This is potentially a very cost-effective pressure mapping imaging solution in particular for imaging large areas. Fabric-based EIT pressure sensors aim to provide a pressure mapping image using current carrying and voltage sensing electrodes attached on the boundary of the fabric patch.

Design/methodology/approach

Recently, promising results are being achieved in conductivity imaging for these sensors. However, the fabric structure presents capacitive behaviour that could also be exploited for pressure mapping imaging. Complex impedance reconstructions with multiple frequencies are implemented to observe both conductivity and permittivity changes due to the pressure applied to the fabric sensor.

Findings

Experimental studies on detecting changes of complex impedance on fabric-based sensor are performed. First, electrical impedance spectroscopy on a fabric-based sensor is performed. Secondly, the complex impedance tomography is carried out on fabric and compared with traditional EIT tank phantoms. Quantitative image quality measures are used to evaluate the performance of a fabric-based sensor at various frequencies and against the tank phantom.

Originality/value

The paper demonstrates for the first time the useful information on pressure mapping imaging from the permittivity component of fabric EIT. Multiple frequency EIT reconstruction reveals spectral behaviour of the fabric-based EIT, which opens up new opportunities in exploration of these sensors.

Details

Sensor Review, vol. 35 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 23 January 2009

Ruzairi Abdul Rahim, Chiam Kok Thiam, Jaysuman Pusppanathan and Yvette Shaan‐Li Susiapan

The purpose of this paper is to view the flow concentration of the flowing material in a pipeline conveyor.

Abstract

Purpose

The purpose of this paper is to view the flow concentration of the flowing material in a pipeline conveyor.

Design/methodology/approach

Optical tomography provides a method to view the cross sectional image of flowing materials in a pipeline conveyor. Important flow information such as flow concentration profile, flow velocity and mass flow rate can be obtained without the need to invade the process vessel. The utilization of powerful computer together with expensive data acquisition system (DAQ) as the processing device in optical tomography systems has always been a norm. However, the advancements in silicon fabrication technology nowadays allow the fabrication of powerful digital signal processors (DSP) at reasonable cost. This allows the technology to be applied in optical tomography system to reduce or even eliminate the need of personal computer and the DAQ. The DSP system was customized to control the data acquisition of 16 × 16 optical sensors (arranged in orthogonal projection) and 23 × 23 optical sensors (arranged in rectilinear projections). The data collected were used to reconstruct the cross sectional image of flowing materials inside the pipeline. In the developed system, the accuracy of the image reconstruction was increased by 12.5 per cent by using new hybrid image reconstruction algorithm.

Findings

The results proved that the data acquisition and image reconstruction algorithm is capable of acquiring accurate data to reconstruct cross sectional images with only little error compared to the expected measurements.

Originality/value

The DSP system was customized to control the data acquisition of 16 × 16 optical sensors (arranged in orthogonal projection) and 23 × 23 optical sensors (arranged in rectilinear projections).

Details

Sensor Review, vol. 29 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 12 July 2011

Stefan Gebhardt and Gernot Scheinert

The purpose of this paper is to calculate the two‐dimensional (2D) centre position of objects with known shapes based on the reconstruction image of a square sensing area…

Abstract

Purpose

The purpose of this paper is to calculate the two‐dimensional (2D) centre position of objects with known shapes based on the reconstruction image of a square sensing area estimated with simulated and measured data by using electrical capacitance tomography (ECT).

Design/methodology/approach

A 2D electrostatic finite element model is used to calculate the capacitances between electrode pairs. A reconstruction algorithm with low computation time provides suitable images for subsequent image processing techniques. The results based on numerical data are verified by measurements.

Findings

It is possible to calculate the centre position of up to four rods (cross‐sectional area about 5 per cent of the measuring area) with an accuracy of 3 per cent in both coordinate directions related to the dimensions of the measuring area.

Originality/value

The paper presents an efficient method for position determination of several objects with known shape and uniform permittivity distribution by using ECT measurements with low‐cost electronic for industrial application.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 30 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 22 May 2008

Alexander D. Klose and Andreas H. Hielscher

This paper sets out to give an overview about state‐of‐the‐art optical tomographic image reconstruction algorithms that are based on the equation of radiative transfer (ERT).

Abstract

Purpose

This paper sets out to give an overview about state‐of‐the‐art optical tomographic image reconstruction algorithms that are based on the equation of radiative transfer (ERT).

Design/methodology/approach

An objective function, which describes the discrepancy between measured and numerically predicted light intensity data on the tissue surface, is iteratively minimized to find the unknown spatial distribution of the optical parameters or sources. At each iteration step, the predicted partial current is calculated by a forward model for light propagation based on the ERT. The equation of radiative is solved with either finite difference or finite volume methods.

Findings

Tomographic reconstruction algorithms based on the ERT accurately recover the spatial distribution of optical tissue properties and light sources in biological tissue. These tissues either can have small geometries/large absorption coefficients, or can contain void‐like inclusions.

Originality/value

These image reconstruction methods can be employed in small animal imaging for monitoring blood oxygenation, in imaging of tumor growth, in molecular imaging of fluorescent and bioluminescent probes, in imaging of human finger joints for early diagnosis of rheumatoid arthritis, and in functional brain imaging.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 18 no. 3/4
Type: Research Article
ISSN: 0961-5539

Keywords

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