• 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.

• 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.

• 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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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.

• 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.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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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

• Journal of Biosystems Engineering
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• v.37 no.5
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• pp.319-326
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• 2012

Purpose: Cheese texture is an important sensory attribute mainly considered for consumers' acceptance. The feasibility of nondestructive measurements of cheese texture was explored using non-contact ultrasonic sensors. Methods: A novel non-contact air instability compensation ultrasonic technique was used for five varieties of hard cheeses to measure ultrasonic parameters, such as velocity and attenuation coefficient. Five texture properties, such as fracturability, hardness, springiness, cohesiveness, and chewiness were assessed by a texture profile analysis (TPA) and correlated with the ultrasonic parameters. Results: Texture properties of five varieties of hard cheese were estimated using ultrasonic parameters with regression analysis models. The most effective model predicted the fracturability, hardness, springiness, and chewiness, with the determination coefficients of 0.946 (RMSE = 21.82 N), 0.944 (RMSE = 63.46 N), 0.797 (RMSE = 0.06 ratio), and 0.833 (RMSE = 17.49 N), respectively. Conclusions: This study demonstrated that the non-contact air instability compensation ultrasonic sensing technique can be an effective tool for rapid and non-destructive determination of cheese texture.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.389-398
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• 2012

Texture is an important visual feature for image analysis. Many approaches have been proposed to model and analyze texture features. Although these approaches significantly contribute to various image-based applications, most of these methods are sensitive to the changes in the scale and orientation of the texture pattern. Because textures vary in scale and orientations frequently, this easily leads to pattern mismatching if the features are compared to each other without considering the scale and/or orientation of textures. This paper suggests an Orientation Matching Scheme (OMS) to ease the problem of mismatching rotated patterns. In OMS, a pair of texture features will be compared to each other at various orientations to identify the best matched direction for comparison. A database including rotated texture images was generated for experiments. A synthetic retrieving experiment was conducted on the generated database to examine the performance of the proposed scheme. We also applied OMS to the similarity computation in a K-means clustering algorithm. The purpose of using K-means is to examine the scheme exhaustively in unpromising conditions, where initialized seeds are randomly selected and algorithms work heuristically. Results from both types of experiments show that the proposed OMS can help improve the performance when dealing with rotated patterns.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1516-1523
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• 2004

The purpose of this study were to analyze the effect of weft knit structural characteristics on the subjective texture and sensibility. For this, the material was knitted into 8 kinds of weft plain knit fabrics with four kinds of fiber components such as wool, acryl, rayon, and nylon, 3 steps of densities and 3 steps of twist numbers to ply two yarns. The data were analyzed by factor analysis, ANOVA and multidimensional scaling. From factor analysis, subjective textures were categorized as 'bulk/resilience', 'surface/density' and 'soft/drape', and subjective sensibilities were categorized as 'natural/comfortable', 'feminine/elegance' and 'stable/neat' Among the knit structural characteristics, the component of fibers and the density of fabrics were the important factors to give variations in texture and sensibility : In comparison with wool knit of medium density, the knit fabrics of other components and different densities each showed a unique texture and sensibility. But twist number to ply two yams had a few influence on subjective properties. As a result of MDS analysis, the texture and sensibility of plain weft knit fabrics was classified as 'thin-full', 'hard-soft', 'young-old' and 'warm-cool'.