Image Reconstruction Using Iterative Transpose Algorithm for Optical Tomography

Yunos, Yusri Md.; Rahim, Ruzairi Abd.; Green, R. G.; Rahiman, Mohd Hafiz Fazalul

doi:10.11113/jt.v47.269

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…The least square method aims to minimize the variation between the

and

for a given electric field distribution in the computational domain. In addition, the transposed Hessian matrix is utilized as a rough approximation instead of using inverse because it is impossible to compute the direct inverse [ 54 ].…”

Section: Solving Inverse Problemmentioning

confidence: 99%

A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images

Ramli

Rahiman

Kamarudin

et al. 2021

Sensors

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This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton’s One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo.

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“…The least square method aims to minimize the variation between the

and

Section: Solving Inverse Problemmentioning

confidence: 99%

A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images

Ramli

Rahiman

Kamarudin

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…It is impossible to compute the direct inverse. Transposed matrix is utilized as a rough approximation instead of inverse [45], [46]. Hence, the NOSER formula is rewritten as in Equation ( 22) for the RTI system.…”

Section: Newton's One-step Error Reconstructionmentioning

confidence: 99%

Enhancing indoor radio tomographic imaging based on minimum RF nodes

Abdullah,

Rahiman,

Khalid

et al. 2024

IJEEI

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Uses the attenuation on the links between transceivers to produce an image using Radio Tomographic Imaging (RTI), a network of transceivers, or a Wireless Sensor Network (WSN). Several RTI setups have been constructed as monitoring areas. However, it is observed that most setups have limitations in the number of RF nodes due to a limited number of measurements. However, it is well known that the main difficulty in radio tomographic imaging attributes to the uncertainties in the RSS measurements of transceivers due to multipath effects, especially, when the environment of interest is much cluttered, and requirements on the larger number of nodes for the performance improvement. It is highly remarkable that the motivation of using fewer nodes in this work is to reduce the deployment cost of radio tomographic imaging, slower data collection rates, longer imaging reconstruction times, and bigger sensitivity matricest, this lead author to proposed to design and development of an RTI system with a minimum of 8 RF nodes. The strong and weak received signal strength (RSS) exhibited in the images will be used to assess the effectiveness and accuracy of human sensing localization in a region. The images were reconstructed based on selected image reconstruction algorithms, and they are Linear Back-Projection (LBP), Filtered Back Projection (FBP), Gaussian, Newton's Onestep's Error Reconstruction (NOSER) and Tikhonov Regularization (TR). The reconstructed images will be analysed using the Mean Structural Similarity (MSSIM) index. A comparison between the algorithms mentioned RTI system based on the MSSIM index. NOSER and TR algorithms scored the highest for the MSSIM index overall experiments, and it is the best technique to produce images that appear similar to the original images.

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Hardware Design of Laser Optical Tomography System for Detection of Bubbles Column

et al. 2013

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This paper presents a hardware design and optical tomography application for fast cross sectional detection of single or two phase flows in pipes or bubble columns. Sixteen laser pointer transmitters and photodiode receivers are arranged at the object cross sectional boundary to detect the existence of bubbles inside a vertical column pipeline. A valve is installed at the bottom of the pipe to produce the source of bubbles. Due to the simple operation, good heat transfer and mass transfer of bubble columns, they can be applied in a wide range of applications in the chemical process industry. The size of the bubbles produced was estimated to be between 5 mm and 20 mm in diameter. The voltage drop at the sensor directly shows the existence of bubbles between the transmitter and receiver.

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Image Reconstruction Using Iterative Transpose Algorithm for Optical Tomography

Cited by 5 publications

References 4 publications

A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images

A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images

Enhancing indoor radio tomographic imaging based on minimum RF nodes

Hardware Design of Laser Optical Tomography System for Detection of Bubbles Column

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