• Title, Summary, Keyword: texture analysis

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Effect of Characteristics and Texture of Sight and Touch on the Tactile Preferences for the Black Fabrics (블랙 패션 소재의 특성과 시촉각적 질감이 촉감 선호도에 미치는 영향)

  • Kim, Yeo-Won;Choi, Jong-Myoung
    • The Research Journal of the Costume Culture
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    • v.19 no.3
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    • pp.556-564
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    • 2011
  • The purpose of this study was to analyze the effect of the structural properties, the color characteristics and the texture of sight and touch on the tactile preferences for the black fabrics. Male and female university students were asked to evaluate the texture of sight and touch and tactile preference to the nine different black fabrics which were selected on the basis of the previous research results. Data were analyzed by using frequency analysis, mean, factor analysis, t-test, F-test, correlation and regression analysis. The texture of sight and touch for black fabrics was classified into four factors: smoothness, bulkiness, extensibility, firmness. This texture of sight and touch factors showed a significant correlative relationship to the structural properties and color characteristics of the black fabrics. There were significant differences according to black fabrics on the point of texture of sight and touch. The velvet was evaluated the most smooth fabric, while the velvet and fake leather were evaluated the most bulky fabrics. Also, the jersey and lace fabrics were evaluated the most extensible fabrics, while the melton was evaluated as the most firm fabrics. There were significant correlative relationships not only between the structural properties and the texture of sight and touch but also between the color characteristics and the texture for black fabrics. Also, among the structural properties, the color characteristics and the texture of sight and touch of black fabrics, major variable factor of influencing on the tactile preference was turned out to be the texture of sight and touch.

Multiple Texture Image Recognition with Unsupervised Block-based Clustering (비교사 블록-기반 군집에 의한 다중 텍스쳐 영상 인식)

  • Lee, Woo-Beom;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.9B no.3
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    • pp.327-336
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    • 2002
  • Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

A Study on the Visual Sensibility of Clothing Texture (의복재질의 시각적 감성연구)

  • 오해순;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.10
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    • pp.1412-1423
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    • 2002
  • The purpose of this study is to objectively explain the visual sensibility of clothing torture that satisfies the consumer's sensibility. The photo stimuli on clothing texture are divided into hard, soft transparent and brilliant. For the study of image 38 kinds of costume samples is used. The Study was measured by using Semantic Differential method. The subjects were 410 females in twenties. The data were analyzed by factor analysis, ANOVA, MDS and regression analysis. Data were analyzed by SPSS. The major findings of this research were as follows: 1. As a result of the factor analysis,5 factors of visual sensibility were consist of high qualities, touches, looks, lightness, and warmness or coolness.2. There were significant difference in visual sensibility based on classification of clothing texture.3. The clothing texture was classified as thin-full, flat-lumpy. 4. As a result of the regression analysis, preferences of consumers can be connected directly with buying behavior and satisfaction can be closely related with preferences and positive buying behavior.

A Study of Texture Through the Depth of Core for BSCCO Superconductor Tape with Pole Figure Analysis (BSCCO 선재에서 극점도를 통한 초전도심의 깊이에 따른 집합조직 연구)

  • 지봉기;주진호;나완수;류경우;박노진
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.14 no.6
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    • pp.499-504
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    • 2001
  • We evaluated the degree of texture through depth of the superconductor core of Bi-Sr-Ca-Cu-O(BSCCO) superconductor tape. The degree of texture was characterized by pole figure analysis indicating that the degree of texture varied significantly with depth of the superconductor core. It was observed that the degree of texture was higher near the interface than inside the superconductor core. Specifically, as getting near to the center from the sheath/core interface, the orientation of BSCCO became dispersed from normal direction(ND) which, in turn, resulted in the degradation of <001>-fiber texture. In addition, the <001> texture was non-uniform an, better texture was developed along rolling direction(RD), compared to transverse direction(TD). Microstructural investigation showed that grain alignment was locally degraded by the existence of second phases. I was observed that larger grain size and better texturing were developed near the relatively straight interface compared to those inside the superconducting core. Based on our study, the region near the interface is thought to carry significant current compared to that inside the core.

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Classification of Textural Descriptors for Establishing Texture Naming System(TNS) of Fabrics -Textural Descriptions of Women's Suits Fabrics for Fall/winter Seasons- (옷감의 질감 명명 체계 확립을 위한 질감 속성자 분류 -여성 슈트용 추동복지의 질감 속성을 중심으로-)

  • Han Eun-Gyeong;Kim Eun-Ae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.30 no.5
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    • pp.699-710
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    • 2006
  • The objective of this study was to identify the texture-related components of woven fabrics and to develop a multidimensional perceptual structure map to represent the tactile textures. Eighty subjects in clothing and tektite industries were selected for multivariate data on each fabric of 30 using the questionnaire with 9 pointed semantic differential scales of 20 texture-related adjectives. Data were analyzed by factor analysis, hierarchical cluster analysis, and multidimensional scaling(MDS) using SPSS statistical package. The results showed that the five factors were selected and composed of density/warmth-coolness, stiffness, extensibility, drapeability, and surface/slipperiness. As a result of hierarchical cluster analysis, 30 fabrics were grouped by four clusters; each cluster was named with density/warmth-coolness, surface/slipperiness, stiffness, and extensibility, respectively. By MDS, three dimensions of tactile texture were obtained and a 3-dimensional perceptual structure map was suggested. The three dimensions were named as surface/slipperiness, extensibility, and stiffness. We proposed a positioning perceptual map of fabrics related to texture naming system(TNS). To classify the textural features of the woven fabrics, hierarchical cluster analysis containing all the data variations, even though it includes the errors, may be more desirable than texture-related multidimensional data analysis based on factor loading values in respect of the effective variables reduction without losing the critical variations.

Simulation of Inhomogeneous Texture through the Thickness Direction during Hot Rolling Deformation in Strip Cast Al-5wt%Mg Alloy (박판 주조된 Al-5 wt%Mg 합금의 열간압연 시 두께방향 불균일 집합조직 시뮬레이션)

  • Song, Young-Sik;Kim, Byoung-Jin;Kim, Hyoung-Wook;Kang, Seok-Bong;Choi, Shi-Hoon
    • Korean Journal of Metals and Materials
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    • v.46 no.3
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    • pp.135-143
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    • 2008
  • The inhomogeneous texture through the thickness direction can be developed during hot rolling deformation in aluminum alloy. In this study, the inhomogeneous texture evolution through the thickness direction during hot rolling deformation in Al-5 wt%Mg alloy produced by a new strip casting technology was measured experimentally. Macrotexture measurement was conducted using X-ray diffractometer. A finite element analysis with ABAQUS/StandardTM and rate sensitive polycrystal model were used to predict the evolution of hot rolling texture. The experimental results of Al-5 wt%Mg alloy were compared with calculated results. The shear texture components tend to be increased at the surface region of the hot-rolled specimen. It is found that triclinic sample symmetry is more accurate assumption for texture analysis and simulation in the surface region of hot-rolled aluminum alloy.

Texture Profile Analysis of Noodle Strands Using a Texture Analyser Interfaced with an IBM-Compatible Computer (컴퓨터를 이용한 동양식 국수의 물성 측정에 관한 연구)

  • Wan Soo Kim
    • Korean journal of food and cookery science
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    • v.8 no.4
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    • pp.397-403
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    • 1992
  • 국수의 물성 측정에 있어서 기존의 방법들은 많은 시간을 요하고 또한 시간 경과에 따른 국수의 물성값에 오차를 주는 단점이 있다. 컴퓨터의 소프트웨어(Xtra)를 이용한 Texture Analyser로 부터 얻어낸 Texture Profile Analysis (TRA)곡선은 국수의 물성변화를 6∼8개의 상수들을 사용해서 설명할 수 있었다. 이 측정방법은 빠르고 효율적이며 시간을 단축할 수 있었다. 그러므로 국수와 파스타(pasta)의 물성 연구에는 이 방법을 도입할 것을 제시하였다.

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Texture Analysis According to Machined Surfaced and Image Magnification (가고면 거칠기와 영상배율에 따른 텍스쳐 해석)

  • 사승윤
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • pp.513-518
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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 carried out through various attempts that were contact or non-contact using computer vision. Even though these efforts, there were few good results in this research. However, texture analysis is making a important role to solve these problems in various fields including universe, aviatiion, living thing and fibers. In this study, texture parameter was obtained by means of position operator according to variation of angle direction and distance. As a result, it was found that surface texture was more effected by direction then distance

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Traversable Region Detection Algorithm using Lane Information and Texture Analysis (차로 수 정보와 텍스쳐 분석을 활용한 주행가능영역 검출 알고리즘)

  • Hwang, Sung Soo;Kim, Do Hyun
    • Journal of Korea Multimedia Society
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    • v.19 no.6
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    • pp.979-989
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    • 2016
  • Traversable region detection is an essential step for advanced driver assistance systems and self-driving car systems, and it has been conducted by detecting lanes from input images. The performance can be unreliable, however, when the light condition is poor or there exist no lanes on the roads. To solve this problem, this paper proposes an algorithm which utilizes the information about the number of lanes and texture analysis. The proposed algorithm first specifies road region candidates by utilizing the number of lanes information. Among road region candidates, the road region is determined as the region in which texture is homogeneous and texture discontinuities occur around its boundaries. Traversable region is finally detected by dividing the estimated road region with the number of lanes information. This paper combines the proposed algorithm with a lane detection-based method to construct a system, and simulation results show that the system detects traversable region even on the road with poor light conditions or no lanes.

Texture Analysis and Classification Using Wavelet Extension and Gray Level Co-occurrence Matrix for Defect Detection in Small Dimension Images

  • Agani, Nazori;Al-Attas, Syed Abd Rahman;Salleh, Sheikh Hussain Sheikh
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2059-2064
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    • 2004
  • Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

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