• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.2
• /
• pp.328-335
• /
• 2010

A hyperspectral imaging spectrometer has shown significant advantages in performance over other existing ones for remote sensing applications. It can collect hundreds of narrow, adjacent spectral bands for each image, which provides a wealth of information on unique spectral characteristics of objects. We have developed a compact hyperspectral imaging system that successively shows high spatial and spectral resolutions and fast data processing performance. In this paper, we present an overview of the hyperspectral imaging system including the strucure of geometrical optics and several image processing schemes such as wavelength calibration and noise reduction for image data on Visible and Near-Infrared(VNIR) and Shortwave-Infrared(SWIR) band.

• Korean Journal of Optics and Photonics
• /
• v.32 no.5
• /
• pp.215-219
• /
• 2021

Recently a system for nondestructive measurement of seedling plants in real time has been attracting attention as an essential element in fields such as the "smart farm". This study reports the simultaneous measurement of anthocyanin accumulations in leaf tissues in a large number of bok choy, using a hyperspectral imaging system. To measure many seedlings simultaneously, an existing hyperspectral imaging system is modified. In this paper, a total of 96 seedlings are measured: 24 each of 4 cultivars. Using the hyperspectral data-acquisition system, 12 seedlings can be analyzed simultaneously within 3 minutes. The hyperspectral imaging technology proposed in this paper is shown to provide an analytic system comparable to destructive chemical analysis. This hyperspectral imaging technology can be applied to a high-throughput plant-phenotyping system, owing to its capability of measuring a large number of specimens at the same time.

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

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.243-246
• /
• 2008

The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high quality spectral and high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems shall be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS shall be calibrated and validated with the calibration equipments such as the integrated sphere and spectral lamps. To improve data quality and availability, it is the most important to understand the mechanism of hyperspectral imaging system and the radiometric and spectral characteristics. This paper presents the major characteristics of camera system on the CAISS and summarizes the results of radiometric and spectral experiment during preliminary system verification.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.213-216
• /
• 2005

A novel hyperspectral imaging spectrometer controlling spatial and spectral resolution individually has been proposed. This imaging spectrometer uses a zoom lens as a telescope and a focusing element. It can change the spatial resolution fixing the spectral resolution or the spectral resolution fixing the spatial resolution. Here, we report the concept of the hyperspectral imaging spectrometer with the novel zooming function and the optical design of a zoom lens as the focusing element. By using lens module and third-order aberration theory, we have presented the initial design of four-group zoom lens with external entrance pupil. And the optimized zoom lens with a focal length of 50 to 150 mm is obtained from the initial design by the optical design software. As a result, the designed zoom lens shows satisfactory performances in wavelength range of 450 to 900 nm as a focusing element in an imaging spectrometer. Furthermore, the collimator lens of the imaging spectrometer is designed through the third-order aberration correction by using an iterative process.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.4
• /
• pp.69-76
• /
• 2015

We present microscopy based hyperspectral imaging system that successively shows high spatial (micrometer) and temporal resolutions (milisecond), and acquired pseudocolor hemoglobin saturation map a result of various image processing techniques can provide additional information such as oxygen transport, abnormal vascularity and therapeutic effects besides structural and physiological measurements in various diseases. To increase understanding of vascular defects several optical methods of imaging for preclinical/clinical assessment have been developed so far. However, they have some limitations for outcoming resolution and user satisfaction level compared to its cost. A hyperspectral imaging system has shown a wide range of vascular characteristics associated with hypervascularity, aberrant angiogenesis or abnormal vascular remodeling in many diseases. This vascular characteristic is considered as a key component to diagnose and detect a type of disease as evidenced by them.

• Journal of Biosystems Engineering
• /
• v.37 no.6
• /
• pp.411-419
• /
• 2012

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

• Korean Journal of Agricultural Science
• /
• v.47 no.3
• /
• pp.633-644
• /
• 2020

Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1^st and 2^nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

• Food Science of Animal Resources
• /
• v.38 no.2
• /
• pp.362-375
• /
• 2018

This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control.

• Korean Journal of Remote Sensing
• /
• v.24 no.5
• /
• pp.397-408
• /
• 2008

A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.