• Korean Journal of Metals and Materials
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• v.47 no.5
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• pp.274-282
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• 2009

To investigate the evolution of deformation texture in dual phase (DP) steels during deep-drawing deformation, deep-drawing experiments were performed. Microtexture measurements were conducted using electron backscattered diffraction (EBSD) to analyze texture evolution. A rate-sensitive polycrystal model was used to predict texture evolution during deep-drawing deformation. In order to evaluate the strain path during deep-drawing deformation, a steady state was assumed in the flange part of a deep-drawn cup. A ratesensitive polycrystal model successfully predicted the texture evolution in DP steels during deep-drawing deformation. The final stable orientations were found to be strongly dependent on the initial location in the blank. Texture analysis revealed that the deep drawability of DP steels decreases as the true strain in the radial direction of the deep-drawn cup increases during deep-drawing deformation.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.38-41
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• 2008

To investigate the evolution of microstructure and texture in AZ31 Mg alloy, direct/indirect extrusion process was carried out at $300^{\circ}C$ with various extrusion speeds. The distribution of grain size depends on extrusion method and extrusion speed. More homogeneous grain site can be obtained at higher extrusion speed of indirect extrusion process. Extrusion speed does not affect significantly texture evolution during extrusion process regardless of extrusion method. ODF section is more useful to understand texture evolution during extrusion process compared with pole figure.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.49-56
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• 1998

Super precision working technique and machine tool have been continually developed thanks to advanced electronic field. To obtain good result. it is necessary to investigate surface in grinding with $mu extrm{m}$ level. There were quite many researches to satisfy these demands by using non-contact methods through the computer vision. In this study, the texture of working surface was analyzed. co-occurrence matrices was obtained from the surface roughness. Texture parameter was obtained using position operator composed of $ heta$, d according to variation of angle direction and distance. As a result, it was found that surface texture was more affected by direction($\theta$) than distance(d).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.144-150
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• 2000

Surface roughness is one of the most important parameters to estimate quality of products. As this reason so many studies were car-ried out through various attempts that were contact or non-contact using computer vision. Even through these efforts there were few good results in this research., however texture analysis making a important role to solve these problems in various fields including universe aviation living thing and fibers. In this study feature value of co-occurrence matrix was calculated by statistic method and roughness value of worked surface was classified, of it. Experiment was carried out using input vector of neural network with characteristic value of texture calculated from worked surface image. It's found that recognition rate of 74% was obtained when adapting texture features. In order to enhance recogni-tion rate combination type in characteristics value of texture was changed into input vector. As a result high recognition rate of 92.6% was obtained through these processes.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.04a
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• pp.22-26
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• 1987

Texture provides an important acurce of information about the threedicensfornarry information of visible surface particulary for stationary conccular views. To recover three dicmensinoary information, the distorging effects of pro jection must be distinguished from properties of the texture on which the distrortion acts. In this paper, we show an approximated maximum likelihood estimation method by which we find surface oriemtation of the visible surface in gaussian sphere using local analysis of the texture, In addition assuming that an orthographic projection and a circle is an image formation system and a texel(texture element)respectively we derive the surface orientation from the distribution of variation by means of orthographic pro jemction of a tangent directon which exstis regulary in the are length of a circle we present the orientation parameters of textured surface with saint and tilt and also the surface normal of the resvlted surface orimentation as needle map. This algorithm was applied to geograghic contour and synthetic textures.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.316-322
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• 1998

Super precision working technique and machine tool have been developing continually thanks to advanced electronic field. To obtain good result. it is necessary to investigate surface state in grinding with ${\mu}{\textrm}{m}$ level. There were so many researches to satisfy these demands using non-contact methods through the computer vision. In this study, the texture of working surface was analyzed. cooccurrence matrice was obtained from the surface roughness. Texture parameter was obtained by means of position operator compose of $\theta$. d according to variation of angle direction and distance. As a result, it was found that surface texture was more effected by direction ($\theta$) then distance(d).

• The Korean Journal of Food And Nutrition
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• v.20 no.4
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• pp.427-432
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• 2007

The texture and descriptive sensory characteristics of a Korean rice cake(Karedduk) with added emulsifier were investigated after 2 and 24 hrs of storage at $5^{\circ}C$. The emulsifier, SP, was added at 0, 0.1, 0.5 and 1% levels to the dry rice flour. In the amylogram, the peak viscosity(P), hot paste viscosity(H) and cold paste viscosity(C) of the rice flour with added emulsifier were higher than those of the control. The texture property analysis by a Texture Analyzer revealed that the springiness, cohesiveness and adhesiveness of the Korean rice cake(Karedduk) with added emulsifier were similar to those of the control, while chewiness, gumminess and hardness were lower compared to the control. Also, the hardness by sensory characteristics was significantly different as compared to the control. Lastly, adding emulsifier to the Korean rice cake(Karedduk) was effective at retarding retrogradation.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1661-1664
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• 2000

내용 기반의 비디오 검색에 있어 텍스처는 중요한 변수로 사용될 수 있다. 모든 물체의 표면은 독특한 성질을 보유하고 있으므로, 텍스처는 형상이나 색과 더불어 중요한 변수로 사용될 수 있다. 어떤 영상의 특징을 올바르게 추출하고 잘 분류하여 표현하는 것은 비디오 검색에 있어서 매우 중요하다. Temporal texture는 무한한 시공간적 범위의 복잡하고, 추상적인 움직임 패턴이며 자연 세계에 흔히 나타난다. 그러므로 이를 특징화시킬 수 있고, temporal texture 패턴을 얼마나 잘 이용할 수 있느냐는 비디오 검색의 성능에 많은 영향을 끼칠 수 있다. 본 논문은 temporal texture 모델링들 중 서로 다른 특징을 가진 세 가지의 모델을 선정하여 비교, 분석한다. 특히, 특징 추출의 분류가 정확하게 이루어지느냐에 초점을 맞추어서 분석하였다. 분류의 성능은 두 가지 변수 즉, 어떤 성질의 모델이며 비디오 데이터인가에 따라 달라지게 된다. 이들 모델링이 분류하기까지 걸리는 시간의 차이는 무시할 수 있을 정도의 시간차이므로, 정확도를 위주로 성능을 분석했다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.443-445
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• 2000

모든 물체의 표면은 독특한 성질을 보유하고 있으므로, 비디오 검색에 있어 텍스처는 형상이나 색과 더불어 중요한 변수로 사용될 수 있다. 비디오 검색에 있어서 중요한 것은 어떤 영상의 특징을 올바르게 추출하고 잘 분류하여 표현하는 것이다. Temporal texture는 무한한 시공간적 범위의 복잡하고, 추상적인 움직임 패턴도 특징화시킬 수 있으므로, temporal texture 패턴을 얼마나 잘 이용할 수 있느냐는 비디오 검색의 성능에 많은 영향을 끼칠 수 있다. 본 논문은 temporal texture의 서로 다른 특징을 가진 세 가지의 모델을 선정하여 비교한다. 특히, 특징 추출의 분류가 정확하게 이루어지느냐에 초점을 맞추어서 분석하였다. 분류의 성능은 두 가지 변수 즉, 어떤 성질의 모델이며 비디오 데이터인가에 따라 달라지게 된다. 이들 모델링이 분류하기까지 걸리는 시간의 차이는 무시할 수 있을 정도의 시간차이므로 정확도를 위주로 성능을 분석했다.

• Korean journal of food and cookery science
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• v.26 no.5
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• pp.545-551
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• 2010

In this study, Sulgidduk samples were prepared with 0%, 3%, 5% and 7% yacon powder. Sulgidduk samples were then examined for quality characteristics such as moisture content, general components, color, texture profile analysis, sensory qualities, and sugar content, in order to determine the optimal ratio of yacon powder in the formulation. Regarding the general components of yacon Sulgidduk, the contents of crude protein and lipid decreased as the ratio of yacon powder increased. The L-value for color decreased, whereas a- and b-values increased. In the texture profile analysis, 7%-added yacon showed significantly lower hardness, whereas 7% yacon powder showed the highest values for cohesiveness, springiness, and chewiness. The contents of sucrose, fructose, and glucose in yacon Sulgidduk were found to be 3%, 5%, and 7% by LC, respectively. Sucrose showed a decreasing trend with increased yacon powder content, but fructose and glucose increased with increased amount of yacon powder. For sensory qualities, taste/flavor, texture, hardness, and overall acceptability were not significantly different among the 0%, 3%, and 5% yacon powder samples.