• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.8
• /
• pp.159-165
• /
• 2015

In this paper, we designed and tested of the passive millimeter-wave imaging system in near range. The proposed passive millimeter-wave imaging system consists two parts. The first part is a 94 GHz band millimeter imaging sensor which is coupled to an antenna, two LNAs, and a diode detector. The second part is a control unit. The control unit is consists of the 2-axes Cartesian robot, the data acquisition (DAQ), and imaging program. The 2-axes Cartesian robot should be able to scan a 2-D image of the metalic tools, IC card and plastic objects, with a raster scanning method. The passive millimeter-wave image of $20{\times}20$ pixels is acquired within less than 60s, and is immediately displayed and stored for post processing.In order to improve the image quality, interpolation methods are applied.

• Journal of electromagnetic engineering and science
• /
• v.17 no.3
• /
• pp.113-119
• /
• 2017

The application of compressive sensing (CS) to a radar imaging system based on a frequency-scanned microstrip leaky wave antenna is investigated. First, an analytical model of the system matrix is formulated as the basis for the inversion algorithm. Then, $L_1-norm$ minimization is applied to the inverse problem to generate a range-azimuth image of the scene. Because of the antenna length, the near-field effect is considered in the CS formulation to properly image close-in targets. The resolving capability of the combined frequency-scanned antenna and CS processing is examined and compared to results based on the short-time Fourier transform and the pseudo-inverse. Both simulation and measurement data are tested to show the system performance in terms of image resolution.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1521-1521
• /
• 2001

The objective of the research being presented was to construct and calibrate a spectrometer for the analysis of single kernels of corn. In light of the difficulties associated with capturing the spatial variability in composition of corn kernels by single-beam spectrometry, a hyperspectral imaging spectrometer was constructed with the intention that it would be used to analyze single kernels of corn for the prediction of moisture and oil content. The spectrometer operated in the range of 750- 1090 nanometers. After evaluating four methods of standardizing the output from the spectrometer, calibrations were made to predict whole-kernel moisture and oil content from the hyperspectral image data. A genetic algorithm was employed to reduce the number of wavelengths imaged and to optimize the calibrations. The final standard errors of prediction during cross-validation (SEPCV) were 1.22% and 1.25% for moisture and oil content, respectively. It was determined, by analysis of variance, that the accuracy and precision of single-kernel corn analysis by hyperspectral imaging is superior to the single kernel reference chemistry method (as tested).

• Imaging Science in Dentistry
• /
• v.51 no.2
• /
• pp.107-115
• /
• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• The Journal of Engineering Geology
• /
• v.31 no.4
• /
• pp.479-492
• /
• 2021

We conducted a fundamental study on geological and rock detection via drone-based hyperspectral imaging on various types of small rock samples and interpreted the obtained information to compare and classify rocks. Further, we performed hyperspectral imaging on ten rocks, and compared the peak data value and reflectance of rocks. Results showed a difference in the reflectance and data value of the rocks, indicating that the rock colors and minerals vary or the reflectance is different owing to the luster of the surface. Among the rocks, limestone used for hyperspectral imaging is grayish white, inverted rock contains various sizes and colors in the dark red matrix, and granite comprises colorless minerals, such as white, black, gray, and colored minerals, resulting in a difference in reflectance. The reflectance of the visible ray range in ten rocks was 16.00~85.78%, in the near infrared ray range, the average reflectance was 23.94~86.43%, the lowest in basalt and highest in marble in both cases. This is because of the pores in basalt, which caused the difference in reflectance.

• Korean Journal of Agricultural Science
• /
• v.50 no.4
• /
• pp.883-902
• /
• 2023

Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.22 no.11
• /
• pp.1054-1062
• /
• 2011

This study describes the time domain imaging algorithm which can be well applied to short-range UWB(ultra wideband) bistatic radar. In the imaging method of SAR technology, the frequency domain method is well applied to the areas which satisfy far-field condition. However in the near-field environment, the image quality is not good due to phase error. However back-projection method based on time domain is well applied to short-range imaging radar. Meanwhile because its processing time is very long, real time-processing is very difficult. To resolve this problem FFBP(Fast Factorized Back-Projection) was proposed. Using the raw data gathered on field we implemented back-projection and FFBP method. Then image quality and processing time were analyzed using these methods.

• Transactions of the Society of Information Storage Systems
• /
• v.9 no.1
• /
• pp.17-21
• /
• 2013

Optical coherence tomography (OCT) allows non-invasive, cross-sectional optical imaging of biological tissue with high spatial resolution and acquisition speed. In principle, it is analogous to ultrasound imaging, but uses near-infrared light instead of ultrasound, measuring the time-delay of back-scattered light from within biological tissue. Compared to ultrasound imaging, it exhibits superior spatial resolution (1~10 um) and high sensitivity. Therefore, OCT has been applied to a wide range of applications such as cellular imaging, ophthalmology and cardiology. Here, we describe a novel application of OCT technology in visualizing microneedles embedded in tissue that is developed to deliver drugs into the dermis without the injection mark in the human skin. Detailed three-dimensional structural images of microneedles and biological tissues were obtained. Examining structural modification of microneedles and tissues during insertion process would enable to evaluate performance of various types of microneedles in situ.

• Journal of Sensor Science and Technology
• /
• v.30 no.2
• /
• pp.76-81
• /
• 2021

In this study, we propose a machine vision system with a high object recognition rate. By utilizing a multiple-exposure image sensing technique, the proposed deep learning-based machine vision system can cover a wide light intensity range without further learning processes on the various light intensity range. If the proposed machine vision system fails to recognize object features, the system operates in a multiple-exposure sensing mode and detects the target object that is blocked in the near dark or bright region. Furthermore, short- and long-exposure images from the multiple-exposure sensing mode are synthesized to obtain accurate object feature information. That results in the generation of a wide dynamic range of image information. Even with the object recognition resources for the deep learning process with a light intensity range of only 23 dB, the prototype machine vision system with the multiple-exposure imaging method demonstrated an object recognition performance with a light intensity range of up to 96 dB.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.6
• /
• pp.441-446
• /
• 2014

A 3D ultrasound image is desired in many medical examinations. However, the implementation of a 2D array, which is needed for a 3D image, is challenging with respect to fabrication, interconnection and cabling. A 2D sparse array, which needs fewer elements than a dense array, is a realistic way to achieve 3D images. Because the number of ways the elements can be placed in an array is extremely large, a method for optimizing the array configuration is needed. Previous research placed the target point far from the transducer array, making it impossible to optimize the array in the operating range. In our study, we focused on optimizing a 2D sparse array transducer for 3D imaging by using a simulated annealing method. We compared the far-field optimization method with the near-field optimization method by analyzing a point-spread function (PSF). The resolution of the optimized sparse array is comparable to that of the dense array.