• Title/Summary/Keyword: surface extraction

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Optimization of Extraction Process Conditions of Aga Soybean Using Response Surface methodology (반응표면분석을 이용한 아가콩의 추출조건 최적화)

  • Lee, Jin-Man;La, Im-Joung;Lee, Do-Sang;Kim, Hwa-Jung;Kim, Young-Il;Lee, Hyung-min;Hur, Sang-Sun
    • Journal of the Korean Applied Science and Technology
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    • v.38 no.6
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    • pp.1699-1708
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    • 2021
  • Response surface methodology was applied to determine the optimum extract conditions(extract temperature and time) for the high-quality Agakong beverage. The optimal roasting condition for Agakong was set at 250 ℃ for 30 minutes. As quality criteria of Agakong, pH, color values and isofavone contents with extract temperature and extract time, the probability value (p<0.01) demonstrated a high significance for the regression model. It was found that the higher the extraction temperature and the longer the extraction time, the higher the isoflavones content. The optimized conditions of extraction isoflavones from agakong were found to be optimized ratio of extraction temperature 99.5℃, extraction time 1.7 h and the maximum rutin yield was 10.63 ㎍/mL.

Extractions of Surface-Active Substances from Defatted Rapeseed Meal (Brassica napus L.) by Supercritical Carbon Dioxide (초임계 CO2 유체 추출법을 이용한 탈지 유채박 중 표면활성물질 추출의 최적화)

  • Kim, Jeong-Won;Jeong, Yong-Seon;Gil, Na-Young;Lee, Eui-Seok;Lee, Yong-Hwa;Jang, Young-Seok;Lee, Ki-Teak;Hong, Soon-Taek
    • The Korean Journal of Food And Nutrition
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    • v.26 no.4
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    • pp.831-840
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    • 2013
  • In this study, an attempt is being made to extract surface-active substances from defatted rapeseed cakes by supercritical carbon dioxide fluid. Independent variables for the extraction process, being formulated by D-optimal design, are pressure (150~350 bar), temperature ($33{\sim}65^{\circ}C$ and co-solvent (ethanol, 50~250 g). The dependent variables of the extraction yield, the content of neutral lipids, phospholipids and glycolipids in the extracts were analyzed upon the results through the response surface methodology. As for the extraction yield, it was found to increase with increasing independent variables, among which the co-solvent proved to be a major influencing parameter. Similar trends were found for the content of surface-active substances (i.e, phospholipids and glycolipids) in the extracts, except for the content of neutral lipids. Regression equations were suggested to coincide well with the results from the experiments. Extraction conditions are being optimized to maximize the extraction yields, the content of phospholipids, and glycolipids were 350 bar (pressure), $65^{\circ}C$ (temperature) and 228.55 g (co-solvent), respectively.

Development of surface defect inspection algorithms for cold mill strip using tree structure (트리 구조를 이용한 냉연 표면흠 검사 알고리듬 개발에 관한 연구)

  • Kim, Kyung-Min;Jung, Woo-Yong;Lee, Byung-Jin;Ryu, Gyung;Park, Gui-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.365-370
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    • 1997
  • In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

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3D image processing using laser slit beam and CCD camera (레이저 슬릿빔과 CCD 카메라를 이용한 3차원 영상인식)

  • 김동기;윤광의;강이석
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.40-43
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    • 1997
  • This paper presents a 3D object recognition method for generation of 3D environmental map or obstacle recognition of mobile robots. An active light source projects a stripe pattern of light onto the object surface, while the camera observes the projected pattern from its offset point. The system consists of a laser unit and a camera on a pan/tilt device. The line segment in 2D camera image implies an object surface plane. The scaling, filtering, edge extraction, object extraction and line thinning are used for the enhancement of the light stripe image. We can get faithful depth informations of the object surface from the line segment interpretation. The performance of the proposed method has demonstrated in detail through the experiments for varies type objects. Experimental results show that the method has a good position accuracy, effectively eliminates optical noises in the image, greatly reduces memory requirement, and also greatly cut down the image processing time for the 3D object recognition compared to the conventional object recognition.

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Generation of 3D Building Model Using Estimation of Rooftop Surface (Rooftop 평면 추정에 의한 3차원 건물 모델 발생)

  • Kang, Yon-Uk;Woo, Dong-Min
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2921-2923
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    • 2005
  • This paper presents to generate 3D building model using estimation of rooftop surface after 3D line segment extraction using hybrid stereo matching techniques in terms of the co-operation of area-based stereo and feature-based stereo. we first performed a junction extraction from 3D line segment data which was obtained by stereo images, and finally generated building's reliable rooftop surface model using LSE(Least Square Error) method after creating surfaces by grouped and fixed junction points. we generated synthetic images for experimentation by photo-realistic simulation on Avenches data set of Ascona aerial images.

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The Three Dimensional Modeling Method of Structure in Urban Areas using Airborne Multi-sensor Data (다중센서 데이터를 이용한 구조물의 3차원 모델링)

  • Son, Ho-Woong;Kim, Ki-Young;Kim, Young-Kyung
    • Journal of the Korean Geophysical Society
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    • v.9 no.1
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    • pp.7-19
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    • 2006
  • Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

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RoI Extraction for Container Placard Recognition (컨테이너 플래카드 인식을 위한 관심 영역 추출)

  • Heo, Gyeongyong;Lee, Imgeun;Woo, Young Woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.629-630
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    • 2018
  • Containers are fitted with various placards on the surface to indicate the risk of cargo. Since the surface of a container is often not flat and there are many types of placards, finding the placard area can increase the speed of recognition. In this paper, proposed is an area extraction method that can find the placard area deformed by the container surface.

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Classification of Surface Defect on Steel Strip by KNN Classifier (KNN 분류기에 의한 강판 표면 결함의 분류)

  • Kim Cheol-Ho;Choi Se-Ho;Kim Gi-Bum;Joo Won-Jong
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.8 s.185
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    • pp.80-88
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    • 2006
  • This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED illuminator and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of hot rolled steel strip are used to develop KNN (k- Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

Classification of Surface Defects on Steel Strip by KNN Classifier (KNN 분류기에 의한 강판 표면 결함의 분류)

  • Kim C.H.;Choi S.H.;Joo W.J.;Kim K.B.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.379-383
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    • 2005
  • This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED light and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of cold roll steel strips are used to develop KNN (k-Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

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Optimization of Alkali Extraction for Preparing Oat Protein Concentrates from Oat Groat by Response Surface Methodology (반응표면분석법을 이용한 쌀귀리 단백질의 알칼리 추출 공정 최적화)

  • Jeong, Yong-Seon;Kim, Jeong-Won;Lee, Eui-Seok;Gil, Na-Young;Kim, San-Seong;Hong, Soon-Taek
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.43 no.9
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    • pp.1462-1466
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    • 2014
  • In this study, an attempt was made to produce oat protein concentrates from defatted oat groat by alkali extraction. Independent variables formulated by D-optimal design were NaOH concentration (X1, 0.005~0.06 N) for extraction and precipitation pH (X2, pH 4.0~6.0), and the dependent variable was extraction yield (Y1, %). Experimental results were analyzed by response surface methodology to determine optimized extraction conditions. Extraction yield increased both with an increase in NaOH concentration of the extraction solution and when approaching a precipitation pH of 4.9, and NaOH concentrations were a major influencing parameter. Solubility of oat protein concentrates showed a minimum value (i.e., 0.1%) at pH 5 and increased substantially at pH values in the range of ${\leq}$ pH 3 or ${\geq}$ pH 7, reaching a maximum value at pH 11 (i.e., 76%). Regression equation coincided well with the results of the experiment. Optimized extraction conditions to maximize extraction yield were 0.06 N NaOH (X1) for extraction and pH 4.7 (X2) for precipitation.