• Title/Summary/Keyword: texture.

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A Study on the Color and Texture of Fashion Fabrics (패션 소재의 색채 이미지와 질감에 관한 연구)

  • 추선형;김영인
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.2
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    • pp.193-204
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    • 2002
  • Many fashion forecasting companies propose the fashion colors in every season. Modern fashion consumer respond to fashionable trends with utmost sensitivity. Therefore to satisfy the consumer with an trendy image, the fashion design must be found first, as image matters, followed by an analysis of each design element's effect on the total image composition. In previous studies of fashion image, has been discussed the positive correlation between fashion design elements of color, fabric, and form as the central issue. In this thesis, two of the fashion design elements, color and fabric are simultaneously considered to classify the image of fabric in fashion. For the color variables, 10 hues are selected from Munsell's system of color notation, and 12 tones from PCCS color notation., which are currently used in the domestic fashion industry. Texture variables used in this survey are classified by luster, prominence-depression of surface, thickness, and density of fabric. Graduate students from 20 to 50 years old and the specialists in fashion companies participated in the survey. The results of this survey are as follows: 1. The fashion fabric image is classified as 5 main images: 'elegant', 'comfortable', 'characteristic', 'light'and 'simple'. 2. The influence of hue, tone and texture is significant to the fashion fabric image. Following colors, yellow-red, red hues and light grayish, dark grayish tones convey the elegant image. The texture property for the elegant image is luster, thin and low density. Properties of fabric conveying the comfortable image are yellow-red and green-yellow hue, soft, light tones, matte and high density. Furthermore, hue turned out to be a insignificant variables for the unique image, whereas dark grayish, grayish tone, luster and prominent texture convey a unique image. For light image, properties of fabric are blue-green, purple hues, light, bright tones with thin, low density texture. Properties of fabric conveying the simple image are blue-green, purple-blue, green-yellow hues, and strong, vivid tones, with luster and flat texture.

Multi-scale Texture Synthesis (다중 스케일 텍스처 합성)

  • Lee, Sung-Ho;Park, Han-Wook;Lee, Jung;Kim, Chang-Hun
    • Journal of the Korea Computer Graphics Society
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    • v.14 no.2
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    • pp.19-25
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    • 2008
  • We synthesize a texture with different structures at different scales. Our technique is based on deterministic parallel synthesis allowing real-time processing on a GPU. A new coordinate transformation operator is used to construct a synthesized coordinate map based on different exemplars at different scales. The runtime overhead is minimal because this operator can be precalculated as a small lookup table. Our technique is effective for upsampling texture-rich images, because the result preserves texture detail well. In addition, a user can design a texture by coloring a low-resolution control image. This design tool can also be used for the interactive synthesis of terrain in the style of a particular exemplar, using the familiar 'raise and lower' airbrush to specify elevation.

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Intensity Gradient filter and Median Filter based Video Sequence Deinterlacing Using Texture Detection (텍스쳐 감지를 이용한 화소값 기울기 필터 및 중간값 필터 기반의 비디오 시퀀스 디인터레이싱)

  • Kang, Kun-Hwa;Ku, Su-Il;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.4C
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    • pp.371-379
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    • 2009
  • In this paper, we proposed new de-interlacing algorithm for video data using intensity gradient filter and median filter with texture detection in the image block. We first introduce the texture detection. According to texture detection, the current region is determined into smooth region or texture region. In case that the smooth region interpolated by median filter. In addition, in case of the texture region, we calculate missing pixel value using intensity gradient filter. Therefore, we analyze the local region feature using the texture detection and classify each missing pixel into two categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results show that the proposed algorithm performs well with a variety of moving sequences compared with conventional intra-field method in the literature.

Two independent mechanisms mediate discrimination of IID textures varying in mean luminance and contrast (평균밝기와 대비성의 차원으로 구성된 결 공간에서 결 분리에 작용하는 두 가지 기제)

  • 남종호
    • Korean Journal of Cognitive Science
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    • v.10 no.3
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    • pp.39-49
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    • 1999
  • The space of IID([ndependently, Identically Distributed) textures was built with axes of mean luminance and contrast, and studied on what kind of mechanisms were required to mediate texture segregation in this space. The conjecture was tested that one of these mechanisms is sensitive to the differences between the means of textures to be discriminated, whereas the other is sensitive to the differences between variances. The probability of discrimination was measured for various pairs of textures in the lID space The data were well fit by a model in which discrimination depends on two mechanisms whose responses are combined by probability summation. The conjecture was rejected that two mechanisms respectively tuned to mean and variance of texture function in segregation. Discrimination within space is mediated by 2 independent channels however: the 2 independent channels are not exactly tuned to texture mean and variance. One m mechanism was primarily sensitive to texture mean, whereas the other was sensitive to b both texture mean and variance.

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표면 Texture 및 나노 Particle 공정에 의한 III-V 태양전지의 효율 변화

  • Sin, Hyeon-Uk;O, Si-Deok;Lee, Se-Won;Choe, Jeong-U;Sin, Jae-Cheol;Kim, Hyo-Jin
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.320-320
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    • 2012
  • III-V 화합물 태양전지는 실리콘, CdTe, CIGS, 염료, 및 유기 등 다른 태양전지에 비해 1sun 상 30% 이상의 고효율을 갖고 있고 앞으로도 계속 증가할 수 있는 가능성을 갖고 있다. 그 이유는 직접천이형 밴드갭, 높은 이동도 등의 고성능 물질특성과 더불어 3족과 5족의 비율을 조절함으로써 같은 결정구조를 갖고 에너지 밴드갭이 다른 물질들을 만들기에 용의하여, 태양전지 스펙트럼의 넓은 영역을 흡수할 수 있는 장점이 있기 때문이다. 그러나, 셀자체의 물질이 실리콘에 비하여 고가이므로, 고성능이 요구되는 우주 인공위성등에 적용이 되었지만, 2000년대 이후로 집광에 적용가능한 태양전지의 연구를 거듭하여 2005년부터는 값싼 프레넬 렌즈를 이용하여 1sun에 비해 500배 해당하는 빛을 셀에 집광하여 보다 효율을 증가시킴으로써 지상발전용에도 적용가능한 셀을 형성하게 되었다. 더불어 태양전지의 효율을 증가시키기 위한 개선된 구조적 변화의 시도도 많이 이루어지고 있다. 최근 보고에 의하면 실리콘 태양전지의 표면에 texture 또는 나노 구조를 주어 높은 흡수율과 낮은 반사율을 갖게 함으로써 효율을 증가시키는 사례가 많아지고, III-V 화합물 태양전지도 texturing에 의해 증가된 효율을 발표한바 있다. 본 연구에서는 태양전지의 효율을 증가시키기 위하여 III-V 화합물 태양전지 표면에 micro-hole array texture 구조를 형성한 후 나노 particle을 이용한 나노 texture 구조를 형성하였다. Photo-lithography와 chemical wet etching으로 micro-hole array texture 구조를 형성하였으며 micro-hole의 직경은 $5{\sim}20{\mu}m$, hole과 hole의 간격은 $3{\sim}15{\mu}m$로 다양하게 변화를 주었다. 형성된 micro-hole array texture 구조위에 수십 nm 크기의 particle을 만들어 chemical wet etching으로 나노 texture 구조를 형성하였다. 태양전지 표면에 texture 구조가 있는 경우와 없는 경우에 각각 효율을 측정, 비교 분석하였다.

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Image Quality Assessment by Combining Masking Texture and Perceptual Color Difference Model

  • Tang, Zhisen;Zheng, Yuanlin;Wang, Wei;Liao, Kaiyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2938-2956
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    • 2020
  • Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

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 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.

Comparison of Compression Schemes for Real-Time 3D Texture Mapping (실시간 3차원 텍스춰 매핑을 위한 압축기법의 성능 비교)

  • Park, Gi-Ju;Im, In-Seong
    • Journal of the Korea Computer Graphics Society
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    • v.6 no.4
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    • pp.35-42
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    • 2000
  • 3D texture mapping generates highly natural visual effects in which objects appear carved from lumps of materials rather than laminated with thin sheets as in 2D texture mapping. Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirement. Recently, a practical real-time 3D texture mapping technique was proposed in [11], where they attempt to resolve the potential texture memory problem by compressing 3D textures using a wavelet-based encoding method. In this paper, we consider two other encoding schemes that could also be applied to the compression-based 3D texture mapping. In particular, we extend the vector quantization and FXT1 for 3D texture compression, and compare their performance with the wavelet-based encoding scheme.

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Preprocessing Method for Efficient Compression of Patch-based Image (패치 영상의 효율적 압축을 위한 전처리 방법)

  • Lee, Sin-Wook;Lee, Sun-Young;Chang, Eun-Youn;Hur, Nam-Ho;Jang, Euee-S.
    • Journal of Broadcast Engineering
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    • v.13 no.1
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    • pp.109-118
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    • 2008
  • In mapping a texture image into a 3D mesh model for photo-realistic graphic applications, the compression of texture image is as important as geometry of 3D mesh. Typically, the size of the (compressed) texture image of 3D model is comparable to that of the (compressed) 3D mesh geometry. Most 3D model compression techniques are to compress the 3D mesh geometry, rather than to compress the texture image. Well-known image compression standards (i.e., JPEG) have been extensively used for texture image compression. However, such techniques are not so efficient when it comes to compress an image with texture patches, since the patches are little correlated. In this paper, we proposed a preprocessing method to substantially improve the compression efficiency of texture compression. From the experimental results, the proposed method was shown to be efficient in compression with a bit-saving from 23% to 45%.

Evaluation of the Impact of Iterative Reconstruction Algorithms on Computed Tomography Texture Features of the Liver Parenchyma Using the Filtration-Histogram Method

  • Pamela Sung;Jeong Min Lee;Ijin Joo;Sanghyup Lee;Tae-Hyung Kim;Balaji Ganeshan
    • Korean Journal of Radiology
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    • v.20 no.4
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    • pp.558-568
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    • 2019
  • Objective: To evaluate whether computed tomography (CT) reconstruction algorithms affect the CT texture features of the liver parenchyma. Materials and Methods: This retrospective study comprised 58 patients (normal liver, n = 34; chronic liver disease [CLD], n = 24) who underwent liver CT scans using a single CT scanner. All CT images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (IR) (iDOSE4), and model-based IR (IMR). On arterial phase (AP) and portal venous phase (PVP) CT imaging, quantitative texture analysis of the liver parenchyma using a single-slice region of interest was performed at the level of the hepatic hilum using a filtration-histogram statistic-based method with different filter values. Texture features were compared among the three reconstruction methods and between normal livers and those from CLD patients. Additionally, we evaluated the inter- and intra-observer reliability of the CT texture analysis by calculating intraclass correlation coefficients (ICCs). Results: IR techniques affect various CT texture features of the liver parenchyma. In particular, model-based IR frequently showed significant differences compared to FBP or hybrid IR on both AP and PVP CT imaging. Significant variation in entropy was observed between the three reconstruction algorithms on PVP imaging (p < 0.05). Comparison between normal livers and those from CLD patients revealed that AP images depend more strongly on the reconstruction method used than PVP images. For both inter- and intra-observer reliability, ICCs were acceptable (> 0.75) for CT imaging without filtration. Conclusion: CT texture features of the liver parenchyma evaluated using the filtration-histogram method were significantly affected by the CT reconstruction algorithm used.