• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.717-721
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• 2008

This paper proposes an image system that can efficiently measure the spectral reflectance of a scene using RGB cameras and LED light sources. Multispectral imaging system is composed of LED controllers, LED clusters and RGB cameras. It captures full-spectral images at real-time. The system adopts a simple, empirical linear model to estimate the full spectral reflectance at each pixel. Since the model is linear, the reconstruction is efficient and stable. We estimated the spectral reflectance of various scenes using the system and showed the effectiveness of the proposed system.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Journal of Biosystems Engineering
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• v.39 no.2
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• pp.142-149
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• 2014

Purpose: A multispectral algorithm for detection and differentiation of defective (defects on apple skin) and normal Red Delicious apples was developed from analysis of a series of hyperspectral line-scan images. Methods: A fast line-scan hyperspectral imaging system mounted on a conventional apple sorting machine was used to capture hyperspectral images of apples moving approximately 4 apples per second on a conveyor belt. The detection algorithm included an apple segmentation method and a threshold function, and was developed using three wavebands at 676 nm, 714 nm and 779 nm. The algorithm was executed on line-by-line image analysis, simulating online real-time line-scan imaging inspection during fruit processing. Results: The rapid multispectral algorithm detected over 95% of defective apples and 91% of normal apples investigated. Conclusions: The multispectral defect detection algorithm can potentially be used in commercial apple processing lines.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.93-97
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• 2022

Infrared scenes usually contain also spectral information which cannot be resolved using normal single-band infrared cameras. Multispectral infrared imaging cameras give access to the comprehensive information contained within infrared scenes. A Dual-band infrared Camera, a type of multispectral infrared imaging cameras, has the advantage of simple system. A Dual-band Infrared Camera gives access to the spectral information as wells as the temperature information within infrared scenes. Multispectral imaging generally increases the detection and identification performance of a Dual-band Infrared Camera. This paper describes a design of an infrared Camera using a Dual-band Infrared Detector to simultaneously receive infrared radiation from the medium-wave infrared/long-wave infrared(MWIR/LWIR) bands.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.265-270
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• 2012

Purpose: An analytic method to design excitation and emission filters of a multispectral fluorescence imaging system is proposed and was demonstrated in an application to poultry fecal inspection Methods: A mathematical model of a multispectral imaging system is proposed and its system parameters, such as excitation and emission filters, were optimally determined by linear discriminant analysis (LDA). An alternating scheme was proposed for numerical implementation. Fluorescence characteristics of organic materials and feces of poultry carcasses are analyzed by LDA to design the optimal excitation and emission filters for poultry fecal inspection. Results: The most appropriate excitation filter was UV-A (about 360 nm) and blue light source (about 460 nm) and band-pass filter was 660-670 nm. The classification accuracy and false positive are 98.4% and 2.5%, respectively. Conclusions: The proposed method is applicable to other agricultural products which are distinguishable by their spectral properties.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.755-764
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• 1996

A multispectral imaging system with selected wavelength optical filter was demonstrated feasible for food safety inspection. Intensified multispectral images of carcasses were obtained with visible/near-infrared optical filters(542-847 nm wavelengths) and analyzed. The analysis of textural features based on co-occurrence matrices was conducted to determine the feasibility of a multispectral image analyses for discriminating unwholesome poultry carcasses from wholesome carcasses. The mean angular second moment of the wholesome carcasses scanned at 542 nm wavelength was lower than that of septicemic (P$\leq$0.0005) and cadaver(P$\leq$0.0005) carcasses. On the other hand, for the carcasses scanned at 700nm wavelength , the feature values of septicemic and cadaver carcasses were significantly (P$\leq$0.0005) different from wholesome carcasses. The discriminant functions for classifying poultry carcasses into three classes (wholesome, septicemic , cadaver) were developed using linear and quadr tic covariance matrix analysis method. The accuracy of the quadratic discriminant models, expressed in rates of correct classification, were over 90% for the classification of wholesome, septicemic, and cadaver carcasses when textural features from the spectral images scanned at the wavelength of 542 and 700nm were utilized.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.561-565
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• 2011

This paper presents an imaging system for reconstruction of enhanced color images using the conventional Bayer CFA. By extracting various colors such as RGBCY from two sequential images which consist of a image by broadband G channel lens filter and the other image captured without one, the proposed color image reconstruction system can reduce the computational complexity for demosaicking and make high resolution color information without aliasing artifacts. Because the proposed system uses the common Bayer CFA image sensor, fabricating a new type of CFA is not necessary for obtaining a multi-spectral image, which can be easily extensible for applications of multi-spectral imaging. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing demosaicking methods, the proposed camera system showed the significant improvements in the sense of color resolution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.999-1004
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• 2002

This paper presents the color displays using more than three primary colors, for the reproduction of wider color gamut, and high-fidelity color reproduction. First, Natural Vision system, which is currently under development for the natural color reproduction in visual telecommunication applications, is introduced, The natural vision is based on spectrum instead of trichromatic color space, and enables high-fidelity color reproduction using multispectral and multiprimary technologies. Then, sixprimary color projection displays using LCD and DLP, and a four-primary color flat panel display are shown. It is experimentally demonstrated that the color gamut becomes much larger than conventional RGB-based display. In addition, it is proved that the spectral color reproduction using multiprimary display suppresses the influence of observer metamerism, and as a result, the color matching between the display and the real object is well improved.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.546-549
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• 2010

RGB 영상의 색 재현성과 조건등색 등의 한계를 개선하기 위해 다중스펙트럼 영상을 활용하는 연구가 활발히 진행되고 있다. 다중스펙트럼 영상을 측정하기 위해서 흑백카메라와 3 개 이상의 컬러 필터들을 이용한다. 본 연구에서는 LCTF 를 사용하여 400nm 에서 720nm 까지 10nm 단위로 33 개의 필터를 사용한다. 이러한 다중스펙트럼 영상 측정 시스템의 특성화를 수행하기 위해 컬러체커뿐만 아니라 광원정보까지 이용하며, 사물의 스펙트럼 반사율도 추정한다. 따라서 분광방사계 보다 빠르게 영상 기반으로 스펙트럼 반사율을 측정할 수 있다. 다양한 광원 조건에서 특성화를 수행하며, 매번 레퍼런스 차트를 측정할 필요 없이 간단히 광원만 측정해도 되는 것을 보인다. 또한 전경영상에서 원하는 영역을 광원환경이 다른 배경 영상에 합성할 때, 자연스러운 사물의 색 변환이 가능하여 보다 실제에 가까운 합성 영상을 생성한다.