• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3106-3106
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• 2001

Imaging spectrometry or hyperspectral imaging is a recent development that makes possible quantitative and qualitative measurement for food quality and safety. This paper presents the research results that a hyperspectral imaging system can be used effectively for detecting fecal (from duodenum, cecum, and colon) and ingesta contamination on poultry carcasses from the different feed meals (wheat, mile, and corn with soybean) for poultry safety inspection. A hyperspectral imaging system has been developed and tested for the identification of fecal and ingesta surface contamination on poultry carcasses. Hypercube image data including both spectral and spatial domains between 430 and 900 nm were acquired from poultry carcasses with fecal and ingesta contamination. A transportable hyperspectral imaging system including fiber optically fabricated line lights, motorized lens control for line scans, and hypercube image data from contaminated carcasses with different feeds are presented. Calibration method of a hyperspectral imaging system is demonstrated using different lighting sources and reflectance panels. Principal Component and Minimum Noise Fraction transformations will be discussed to characterize hyperspectral images and further image processing algorithms such as image band ratio of dual-wavelength images and its histogram stretching with thresholding process will be demonstrated to identify fecal and ingesta materials on poultry carcasses. This algorithm could be further applied for real-time classification of fecal and ingesta contamination on poultry carcasses in the poultry processing line.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.304-310
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• 2017

In this paper, we propose the architecture of an IPM based lane detector for autonomous vehicles to detect and control the driving route along the curved lane. In the IPM image, we divide the area into two fields, Far/Near Field, and the lane candidate region is detected using the Hough transform to perform the matching for the curved lane. In autonomous vehicles, various algorithms must be embedded in the system. To reduce the system resources, we proposed a method to minimize the number of memory accesses to the image and various parameters on the external memory. The proposed circuit has 96% lane recognition rate and occupies 16% LUT, 5.9% FF and 29% BRAM in Xilinx XC7Z020. It processes Full-HD image at a rate of 42 fps at a 100 MHz operating clock.

• Analytical Science and Technology
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• v.24 no.2
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• pp.85-93
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• 2011

To protect the steel structure in a high story buildings from fire, the sprayed fire-resistive materials are applied during the construction. Current standard methods to check the quality of sprayed fire-resistive materials are real fire test in lab, which take a long time (several weeks) and expensive. In this study, a simple analytical method to check the quality of sprayed fire-resistive materials is developed using Near Infrared Spectroscopy (NIR). Total 9 kinds of sprayed fire-resisted materials and 3 kinds of normal sprayed material sets were used for the analysis. Each set of materials was 50 to 100 samples. Samples are grinded and make a fine powder. The spectral data acquisition was carried out using FT-NIR spectrometer with a integrating sphere. NIR methods successfully identify the sprayed fire resistive materials by a principle component analysis (PCA) after a vector normalization (SNV) pretreatment.

• Korean Journal of Agricultural Science
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• v.41 no.1
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• pp.59-63
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• 2014

Precision farming aims at reduced environmental impacts with increased productivity. Soils are multi-functional media in which air, water and biota occur together and form an essential part of the landscape with a fundamental role in the environment. The requirement for herbicides and fertilizers can vary within a field in response to spatial differences in soil properties. Near infrared (NIR) spectroscopy is widely used today as a nondestructive analytical technique which is capable of determining a number of physio-chemical parameters. The objectives of this study were to develop optimal models to predict chemical properties of paddy soils by visible and NIR reflectance spectra. Total of 60 soil samples were collected in spring from 20 paddy fields within central regions in Korea. Reflectance spectra, moisture contents, pH, total nitrogen (N), organic matter, available phosphate ($P_2O_5$) of soil samples were measured. The reflectance spectra were measured in wavelength ranges of 400-2,500 nm with 2 nm interval. The method of partial least square (PLS) analysis was used to determine the soil properties. The PLS analyses showed good correlation between predicted and measured chemical properties of paddy soils in the wavelength range of 1,800-2,400 nm. Especially, it showed better performance than the previous results which used the entire wavelength range of the spectrophotometer, without considering the optimal wavelength of each soil properties.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.888-897
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• 2015

A flight capability to take a terrain following flight near the ground is required to reduce the probability that a fighter aircraft can be detected by foe's radar fence in the battlefield. The success rate for mission flight has increased by adopting TFS (Terrain Following System) to enable the modern advanced fighter to fly safely near the ground at the low altitude. This system has applied to the state-of-the-art fighter and bomber, such as B-1, F-111, F-16 E/F and F-15, since the research begins from 1960's. In this paper, the terrain following system and GCAS (Ground Collision Avoidance System) was developed, based on a digital database with UTAS's TERPRROM (TERrain PROfile Matching) equipment. This system calculates the relative location of the aircraft in the terrain database by using the aircraft status information provided by the radar altimeter and the INS (Inertial Navigation System), based on the digital terrain database loaded previously in the DTC (Data Transfer Cartridge), and figures out terrain features around. And, the system is a manual terrain following system which makes a steering command cue refer to flight path marker, on the HUD (Head Up Display), for vertical acceleration essential for terrain following flight and enables a pilot to follow it. The cue is based on the recognized terrain features and TCH (Target Clearance Height) set by a pilot in advance. The developed terrain following system was verified in the real-time pilot evaluation in FA-50 HQS (Handling Quality Simulator) environment.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.5
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• pp.387-394
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• 2015

Before salvaging a wrecked ship, the physics-based simulation is needed to predict lifting force before real operation by floating crane or barge. Procedures affecting lifting force for the salvage can be divided into three stages. At the first stage, the bottom breakout force for the wrecked ship to escape from seabed sediment should be calculated. At the second step, the current force acting on the wrecked ship while lifting from the seabed to near sea surface should be considered. Finally, buoyancy change near at the sea surface when the wrecked ship start to escape from the water should be considered. In the previous studies, only the breakout force at the first stage was calculated based on simple assumption of embedment depth and contact area of the wrecked ship. Therefore, we develop a program for salvage simulation including whole stages. It is composed of four modules such as the equations of motion, time integration, force calculation, and visualization. As a result, it is applied to simulate lifting the wrecked ship according to various environmental loads including seabed sediments.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.2
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• pp.92-103
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• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.165-168
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• 2006

Fourier transform-near infrared spectroscopy (FT-NIRS) was evaluated for determination of total dietary fiber (TDF) content of brown rice. Enzymatic-gravimetric method was suitable to obtain reference values for calibration of NIR at 1,000-2,500 nm range. Standard error of laboratory procedure ranged 0.17 to 0.72%. Partial least square (PLS) regression was used to develop the calibration equations. Regression was performed automatically using NIRCal chemometric software. Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP), showing 0.9780, 0.0636, and 0.0642, respectively. This prediction model can be used for determination of TDF in brown rice and would be useful for real-time analysis in food industry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.181-184
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• 2006

Knowledge of the ionospheric peak parameter foF2 (the critical frequency of F2 layer) is one of key essential factors for predicting ionospheric characteristics and delay correction of satellite positioning. However, the foF2 was almost estimated using an empirical model of International Reference Ionosphere (IRI) or other expensive observing techniques, such as ionosondes and scatter radar. In this paper, the ionospheric peak parameter foF2 is the first observed by ground-based GPS with all weather, low-cost and near real time properties. Compared with the IRI-2001 and independent ionosondes at or near the GPS receiver stations, the foF2 obtained from ground-based GPS is in better agreement, but closer to the ionosonde. However, during nighttime, the IRI model overestimated the GPS observed values during winter and equinox months.Furthermore, seasonal variation trend of the foF2 in 2003 is studied using foF2 monthly median hourly data measured over South Korea. It has shown that the systematic diurnal changes of foF2 are apparent in each season and the higher values of foF2 are observed during the equinoxes (semiannual anomaly) as well as in mid-daytime of each season.

• Food Science of Animal Resources
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• v.41 no.4
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• pp.563-588
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• 2021

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.