• Title/Summary/Keyword: Multi-input system

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Analysis of Skin Color Pigments from Camera RGB Signal Using Skin Pigment Absorption Spectrum (피부색소 흡수 스펙트럼을 이용한 카메라 RGB 신호의 피부색 성분 분석)

  • Kim, Jeong Yeop
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.1
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    • pp.41-50
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    • 2022
  • In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

Coastal Shallow-Water Bathymetry Survey through a Drone and Optical Remote Sensors (드론과 광학원격탐사 기법을 이용한 천해 수심측량)

  • Oh, Chan Young;Ahn, Kyungmo;Park, Jaeseong;Park, Sung Woo
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.29 no.3
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    • pp.162-168
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    • 2017
  • Shallow-water bathymetry survey has been conducted using high definition color images obtained at the altitude of 100 m above sea level using a drone. Shallow-water bathymetry data are one of the most important input data for the research of beach erosion problems. Especially, accurate bathymetry data within closure depth are critically important, because most of the interesting phenomena occur in the surf zone. However, it is extremely difficult to obtain accurate bathymetry data due to wave-induced currents and breaking waves in this region. Therefore, optical remote sensing technique using a small drone is considered to be attractive alternative. This paper presents the potential utilization of image processing algorithms using multi-variable linear regression applied to red, green, blue and grey band images for estimating shallow water depth using a drone with HD camera. Optical remote sensing analysis conducted at Wolpo beach showed promising results. Estimated water depths within 5 m showed correlation coefficient of 0.99 and maximum error of 0.2 m compared with water depth surveyed through manual as well as ship-board echo-sounder measurements.

Seismic Behavior of Bridges Considering Ground Motion Spatial Variation (공간적으로 변화하는 입력지진으로 인한 교량의 지진거동특성)

  • Bae, Byung Ho;Choi, Kwang Kyu;Kang, Seung Woo;Song, Si Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.4
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    • pp.759-768
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    • 2015
  • The ground motions of large dimensional structures such as long span bridges at different stations during an earthquake, are inevitably different, which is known as the ground motion spatial variation effect. There are many causes that may result in the spatial variability in seismic ground motion, e.g., the wave passage effect due to the different arrival times of waves at different locations; the loss of coherency due to seismic waves scattering in the heterogeneous medium of the ground; the site amplification effect owing to different local soil properties. In previous researches, the site amplification effects have not been considered or considered by a single-layered soil model only. In this study, however, the ground motion amplification and filtering effects are evaluated by multi-layered soil model. Spatially varying ground motion at the sites with different number of layers, depths, and soil characteristics are generated and the variation characteristics of ground motion time histories according to the correlation of coherency loss function and soil conditions are evaluated. For the bridge system composed of two unit bridges, seismic behavior characteristics are analyzed using the generated seismic waves as input ground motion. Especially, relative displacement due to coherency loss and site effect which can cause the unseating and pounding between girders are evaluated. As a result, considering the soil conditions of each site are always important and should not be neglected for an accurate structural response analysis.

Design of RF Front-end for High Precision GNSS Receiver (고정밀 위성항법 수신기용 RF 수신단 설계)

  • Chang, Dong-Pil;Yom, In-Bok;Lee, Sang-Uk
    • Journal of Satellite, Information and Communications
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    • v.2 no.2
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    • pp.64-68
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    • 2007
  • This paper describes the development of RF front.end equipment of a wide band high precision satellite navigation receiver to be able to receive the currently available GPS navigation signal and the GALILEO navigation signal to be developed in Europe in the near future. The wide band satellite navigation receiver with high precision performance is composed of L - band antenna, RF/IF converters for multi - band navigation signals, and high performance baseband processor. The L - band satellite navigation antenna is able to be received the signals in the range from 1.1 GHz to 1.6 GHz and from the navigation satellite positioned near the horizon. The navigation signal of GALILEO navigation satellite consists of L1, E5, and E6 band with signal bandwidth more than 20 MHz which is wider than GPS signal. Due to the wide band navigation signal, the IF frequency and signal processing speed should be increased. The RF/IF converter has been designed with the single stage downconversion structure, and the IF frequency of 140 MHz has been derived from considering the maximum signal bandwidth and the sampling frequency of 112 MHz to be used in ADC circuit. The final output of RF/IF converter is a digital IF signal which is generated from signal processing of the AD converter from the IF signal. The developed RF front - end has the C/N0 performance over 40dB - Hz for the - 130dBm input signal power and includes the automatic gain control circuits to provide the dynamic range over 40dB.

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Adaptive Mass-Spring Method for the Synchronization of Dual Deformable Model (듀얼 가변형 모델 동기화를 위한 적응성 질량-스프링 기법)

  • Cho, Jae-Hwan;Park, Jin-Ah
    • Journal of the Korea Computer Graphics Society
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    • v.15 no.3
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    • pp.1-9
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    • 2009
  • Traditional computer simulation uses only traditional input and output devices. With the recent emergence of haptic techniques, which can give users kinetic and tactile feedback, the field of computer simulation is diversifying. In particular, as the virtual-reality-based surgical simulation has been recognized as an effective training tool in medical education, the practical virtual simulation of surgery becomes a stimulating new research area. The surgical simulation framework should represent the realistic properties of human organ for the high immersion of a user interaction with a virtual object. The framework should make proper both haptic and visual feedback for high immersed virtual environment. However, one model may not be suitable to simulate both haptic and visual feedback because the perceptive channels of two feedbacks are different from each other and the system requirements are also different. Therefore, we separated two models to simulate haptic and visual feedback independently but at the same time. We propose an adaptive mass-spring method as a multi-modal simulation technique to synchronize those two separated models and present a framework for a dual model of simulation that can realistically simulate the behavior of the soft, pliable human body, along with haptic feedback from the user's interaction.

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Direct Determination of Soil Nitrate Using Diffuse Reflectance Fourier Transform Spectroscopy (DRIFTS) (중적외선 분광학을 이용한 토양 내의 질산태 질소 정량분석)

  • Choe, Eunyoung;Kim, Kyoung-Woong;Hong, Suk Young;Kim, Ju-Yong
    • Korean Journal of Soil Science and Fertilizer
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    • v.41 no.4
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    • pp.267-272
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    • 2008
  • Mid-infrared (MIR) spectroscopy, particularly Fourier transform infrared spectroscopy (FTIR), has emerged as an important analytical tool in quantification as well as identification of multi-atomic inorganic ions such as nitrate. In the present study, the possibility of quantifying soil nitrate via diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) without change of a sample phase or with least treated samples was examined. Four types of soils were spectrally characterized in terms of unique bands of soil contents and interferences with nitrate bands in the range of $2000-1000cm^{-1}$. In order to reduce the effects of soil composition on calibration model for nitrate, spectra transformed to the 1st order derivatives were used in the partial least squared regression (PLSR) model and the classification procedure associated with input soil types was involved in calibration system. PLSR calibration models for each soil type provided better performance results ($R^2$>0.95, RPD>6.0) than the model considering just one type of soil as a standard.

Distribution of Surface Solar Radiation by Radiative Model in South Korea (복사 모델에 의한 남한의 지표면 태양광 분포)

  • Zo, Il-Sung;Jee, Joon-Bum;Lee, Won-Hak;Lee, Kyu-Tae;Choi, Young-Jean
    • Journal of Climate Change Research
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    • v.1 no.2
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    • pp.147-161
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    • 2010
  • The temporal and spatial distributions of surface solar radiation were calculated by the one layer solar radiative transfer model(GWNU) which was corrected by multi layer Line-by-Line(LBL) model during 2009 in South Korea. The aerosol optical thickness, ozone amount, cloud fraction and total precipitable water were used as the input data for GWNU model run and they were retrieved from Moderate Resolution Imaging Spectrometer(MODIS), Ozone Monitoring Instrument(OMI), MTSAT-1R satellite data and the Regional Data Assimilation Prediction System(RDAPS) model result, respectively. The surface solar radiation was calculated with 4 km spatial resolution in South Korea region using the GWNU model and the results were compared with surface measurement(by pyranometer) data of 22 KMA solar sites. The maximum values(more than $5,400MJ/m^2$) of model calculated annual solar radiation were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud amount data. However, the spatial distribution of surface measurement data was comparatively different from the model calculation because of the insufficient correction and management problems for the sites instruments(pyranometer).

A study on user authentication method using speaker authentication mechanism in login process (로그인 과정에서의 화자인증 메커니즘을 이용한 사용자인증 방안 연구)

  • Kim, Nam-Ho;Choi, Ji-Young
    • Smart Media Journal
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    • v.8 no.3
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    • pp.23-30
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    • 2019
  • With the popularization of the Internet and smartphone uses, people in the modern era are living in a multi-channel environment in which they access the information system freely through various methods and media. In the process of utilizing such services, users must authenticate themselves, the typical of which is ID & password authentication. It is considered the most convenient method as it can be authenticated only through the keyboard after remembering its own credentials. On the other hand, modern web services only allow passwords to be set with high complexity by different combinations. Passwords consisting of these complex strings also increase proportionally, since the more services users want to use, the more user authentication information they need to remember is recommended periodically to prevent personal information leakage. It is difficult for the blind, the disabled, or the elderly to remember the authentication information of users with such high entropy values and to use it through keyboard input. Therefore, this paper proposes a user authentication method using Google Assistant, MFCC and DTW algorithms and speaker authentication to provide the handicapped users with an easy user authentication method in the login process.

Design and Implementation of OpenCV-based Inventory Management System to build Small and Medium Enterprise Smart Factory (중소기업 스마트공장 구축을 위한 OpenCV 기반 재고관리 시스템의 설계 및 구현)

  • Jang, Su-Hwan;Jeong, Jopil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.161-170
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    • 2019
  • Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

Land Cover Classification of High-Spatial Resolution Imagery using Fixed-Wing UAV (고정익 UAV를 이용한 고해상도 영상의 토지피복분류)

  • Yang, Sung-Ryong;Lee, Hak-Sool
    • Journal of the Society of Disaster Information
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    • v.14 no.4
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    • pp.501-509
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    • 2018
  • Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.