• Title/Summary/Keyword: reflectance model

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Shape Recognition of a BGA Ball using Ring Illumination (링 조명에 의한 BGA 볼의 3차원 형상 인식)

  • Kim, Jong Hyeong;Nguyen, Chanh D.Tr.
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.960-967
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    • 2013
  • Shape recognition of solder ball bumps in a BGA (Ball Grid Array) is an important issue in flip chip bonding technology. In particular, the semiconductor industry has required faster and more accurate inspection of micron-size solder bumps in flip chip bonding as the density of balls has increased dramatically. The difficulty of this issue comes from specular reflection on the metal ball. Shape recognition of a metal ball is a very realproblem for computer vision systems. Specular reflection of the metal ball appears, disappears, or changes its image abruptly due to tiny movementson behalf of the viewer. This paper presents a practical shape recognition method for three dimensional (3-D) inspection of a BGA using a 5-step ring illumination device. When the ring light illuminates the balls, distinctive specularity images of the balls, which are referred to as "iso-slope contours" in this paper, are shown. By using a mathematical reflectance model, we can drive the 3-D shape information of the ball in aquantitative manner. The experimental results show the usefulness of the method for industrial application in terms of time and accuracy.

Discrimination of geographical origin and cultivation years of Ginseng by near Infrared reflectance spectroscopy

  • Lin, Guo-Lin;Sohn, Mi-Ryeong;Cho, Rae-Kwnag;Hong, Jin-Hwan
    • Near Infrared Analysis
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    • v.1 no.2
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    • pp.41-44
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    • 2000
  • The objectives of this study are to discriminate the geographical origin and cultivation years of ginseng based on the near-infrared(NIR) reflectance spectroscopic analysis. Korea and China ginseng samples were prepared for discrimination of geographical origin. 4, 5 and 6 years-old ginseng samples from Korea were prepared for discrimination of cultivation years. Used spectrometer were InfraAlyzer 500, InfraAlyzer 400 and Fiber optic. Sample type of ginseng was 3, whole ginseng radix, slide section and powder type. The accuracy was affected by sample types and instruments. The accuracy for discrimination geographical origin was 97% in calibration model using IA 500 and ginseng powder. For discrimination of cultivation years, the model with slide selection using IA500 were relative accurate. The accuracy was 96.7% for 4-year, 91.3% for 5-year and 89.3% for 6-year old ginseng. The study shows that NIR spectroscopic analysis can be used to discriminate the geographical origin and cultivation years of ginseng with acceptable accuracy.

Prediction of Soluble Solid and Firmness in Apple by Visible/Near-Infrared Spectroscopy (가시광선/근적외선 분광분석법을 이용한 사과의 당도 및 경도 측정)

  • 최창현;이강진;박보순
    • Journal of Biosystems Engineering
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    • v.22 no.2
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    • pp.256-265
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    • 1997
  • The objectives of this study were to examine the ability to predict soluble solid and firmness in intact apples based on the visible/near-infrared spectroscopic technique. Two cultivars of apples, Delicious and Gala, were handled, tested and analyzed separately. Reflectance spectra, Magness-Tayor (MT) firmness, and soluble solids in apples were measured sequentially. Maximum and minimum diameters, height, and weight of apples were recorded before the MT firmness tests. A spectrophotometer was used to collect reflectance spectra of intact apples over a wavelength range of 400 to 2, 498 nm. The W firmness tests were conducted using a standard 11.1mm (7/16 in.) MT probe mounted in an Instron universal testing machine. A digital refractormeter was used to measure soluble solid contents in the apples. Apple samples were divided into a calibration set and a prediction set. The calibration set was used during model development, and the prediction set was used to predict soluble solids and firmness from unknown spectra. The method of partial least square (PLS) analysis was used. An unique set of PLS loading vectors (factors) was developed for soluble solid content and firmness. The PLS model showed good correlations between predicted and measured soluble solids of intact apples in 860~1078 nm of the wavelengths. However, the PLS analysis was not good enough to predict the apple firmness.

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Stochastic Estimation of Acoustic Impedance of Glass-Reinforced Epoxy Coating

  • Kim, Nohyu;Nah, Hwan-Seon
    • Journal of the Korean Society for Nondestructive Testing
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    • v.34 no.2
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    • pp.119-127
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    • 2014
  • An epoxy coating applied to the concrete surface of a containment building deteriorates in hazardous environments such as those containing radiation, heat, and moisture. Unlike metals, the epoxy coating on a concrete liner absorbs and discharges moisture during the degradations process, so it has a different density and volume during service. In this study, acoustic impedance was adopted for characterizing the degradation of a glass-reinforced epoxy coating using the acoustic reflection coefficient (reflectance) on a rough epoxy coating. For estimating the acoustic reflectance on a wavy epoxy coating surface, a probabilistic model was developed to represent the multiple irregular reflections of the acoustic wave from the wavy surface on the basis of the simulated annealing technique. A number of epoxy-coated concrete specimens were prepared and exposed to accelerated aging conditions to induce an artificial aging degradation in them. The acoustic impedance of the degraded epoxy coating was estimated successfully by minimizing the error between a waveform calculated from the mathematical model and a waveform measured from the surface of the rough coating.

Cast Shadow Extraction of Mountainous Terrain in Satellite Imagery (위성영상에서 산악지역의 그림자 추출)

  • 손홍규;윤공현;송영선
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.309-312
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    • 2004
  • In mountainous area with high relief, topography may cause cast shadows due to the blocking of direct solar radiation. Remote sensing images of these landscapes display reduced values of reflectance for shadowed areas compared to non-shadowed areas with similar surface cover characteristics. A variety of approaches are possible, though a common step in various active approaches is first to delineate the shadows using automated algorithm and digital surface model (or digital elevation model). This articles demonstrates a common confusion caused by cast shadows

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Estimation of Chlorophyll-a Concentrations in the Nakdong River Using High-Resolution Satellite Image (고해상도 위성영상을 이용한 낙동강 유역의 클로로필-a 농도 추정)

  • Choe, Eun-Young;Lee, Jae-Woon;Lee, Jae-Kwan
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.613-623
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    • 2011
  • This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with $R^2$ 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with $R^2$ 0.66 and 0.73, respectively. Their performance showed the 'Approximate Prediction' with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.

Classification of Sedimentary Facies Using IKONOS Image in Hwangdo Tidal Flat, Cheonsu Bay (IKONOS 영상을 이용한 천수만 황도 갯벌 표층 퇴적상 분류)

  • Ryu, Joo-Hyung;Woo, Han Jun;Park, Chan-Hong;Yoo, Hong-Rhyong
    • Journal of Wetlands Research
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    • v.7 no.2
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    • pp.121-132
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    • 2005
  • To classify the surface sedimentary facies using IKONOS image collected over Hwangdo tidal flat in Cheonsu Bay, the optical reflectance was compared for characterizing various sedimentary environments such as grain size, tidal channel pattern and area ratio of surface remnant water. The intertidal DEM (Digital Elevation Model) was generated by echo-sounder for analyzing the relationship between IKONOS image and sedimentary environments including topography. The boundary of the optical reflectance between mud-mixed facies and sand facies was distinct, and discrimination of the associated sandbar feature was also possible. The mud-mixed facies coupled with intricate tidal channels is confined to the relatively hi호 topography of Hwangdo tidal flat. The boundary between mud and mixed flat was indistinct in IKONOS optical reflectance but it would have a difference in the area ratio of surface remnant water. The dark area in the image represented the well developed sand facies having a lot of surface remnant water due to the relatively low surface topography. The overall accuracy of characterizing the surface sediment facies by maximum likelihood classification method was 86.2 %. These results demonstrate that high spatial resolution satellite imagery such as IKONOS coupled with knowledge of grain size, surface remnant water and tidal channel network can be effectively used to characterize the surface sedimentary facies (mud, mixed and sand) network of the tidal flat environments.

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Analysis of the Impact of Surface Reflectance Error Retrieved from 6SV for KOMPSAT-3A according to MODIS AOD Expected Error (MODIS AOD 기대 오차에 따른 6SV 기반 KOMPSAT-3A 채널별 지표반사도 오차 영향 분석)

  • Daeseong Jung;Suyoung Sim;Jongho Woo;Nayeon Kim;Sungwoo Park;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1517-1522
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    • 2023
  • This study evaluates the impact of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) expected error (EE) on the accuracy of surface reflectance (SR) derived from the KOMPSAT-3A satellite, utilizing the Second Simulation of the Satellite Signal in the Solar Spectrum Vector radiative transfer model. By considering a range of ground-based AOD and the resultant MODIS AOD EE, the research identifies significant influences on SR accuracy, particularly under high solar zenith angles(SZA) and shorter wavelengths. The study's simulations reveal that SR errors increase with shorter wavelengths and higher SZAs, highlighting the necessity for further research to improve atmospheric correction algorithms by incorporating wavelength and SZA considerations. Additionally, the study provides foundational data for better understanding the use of AOD data from other satellites in atmospheric correction processes and contributes to advancing atmospheric correction technologies.

An Experiment for Surface Reflectance Image Generation of KOMPSAT 3A Image Data by Open Source Implementation (오픈소스 기반 다목적실용위성 3A호 영상자료의 지표면 반사도 영상 제작 실험)

  • Lee, Kiwon;Kim, Kwangseob
    • Korean Journal of Remote Sensing
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    • v.35 no.6_4
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    • pp.1327-1339
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    • 2019
  • Surface reflectance obtained by absolute atmospheric correction from satellite images is useful for scientific land applications and analysis ready data (ARD). For Landsat and Sentinel-2 images, many types of radiometric processing methods have been developed, and these images are supported by most commercial and open-source software. However, in the case of KOMPSAT 3/3A images, there are currently no tools or open source resources for obtaining the reflectance at the top-of-atmosphere (TOA) and top-of-canopy (TOC). In this study, the atmospheric correction module of KOMPSAT 3/3A images is newly implemented to the optical calibration algorithm supported in the Orfeo ToolBox (OTB), a remote sensing open-source tool. This module contains the sensor model and spectral response data of KOMPSAT 3A. Aerosol measurement properties, such as AERONET data, can be used to generate TOC reflectance image. Using this module, an experiment was conducted, and the reflection products for TOA and TOC with and without AERONET data were obtained. This approach can be used for building the ARD database for surface reflection by absolute atmospheric correction derived from KOMPSAT 3/3A satellite images.

Development of Artificial Intelligence-Based Remote-Sense Reflectance Prediction Model Using Long-Term GOCI Data (장기 GOCI 자료를 활용한 인공지능 기반 원격 반사도 예측 모델 개발)

  • Donguk Lee;Joo Hyung Ryu;Hyeong-Tae Jou;Geunho Kwak
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1577-1589
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    • 2023
  • Recently, the necessity of predicting changes for monitoring ocean is widely recognized. In this study, we performed a time series prediction of remote-sensing reflectance (Rrs), which can indicate changes in the ocean, using Geostationary Ocean Color Imager (GOCI) data. Using GOCI-I data, we trained a multi-scale Convolutional Long-Short-Term-Memory (ConvLSTM) which is proposed in this study. Validation was conducted using GOCI-II data acquired at different periods from GOCI-I. We compared model performance with the existing ConvLSTM models. The results showed that the proposed model, which considers both spatial and temporal features, outperformed other models in predicting temporal trends of Rrs. We checked the temporal trends of Rrs learned by the model through long-term prediction results. Consequently, we anticipate that it would be available in periodic change detection.