• Title/Summary/Keyword: texture image

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Image Retrieval using Fast Wavelet Histogram and Color Information (고속 웨이블렛 히스토그램과 색상정보를 이용한 영상검색)

  • 김주현;이배호
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.194-197
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    • 2000
  • Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

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An Image Coding Technique Using the Image Segmentation (영상 영역화를 이용한 영상 부호화 기법)

  • 정철호;이상욱;박래홍
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.5
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    • pp.914-922
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    • 1987
  • An image coding technique based on a segmentation, which utilizes a simplified description of regions composing an image, is investigated in this paper. The proposed coding technique consists of 3 stages: segmentation, contour coding. In this paper, emphasis was given to texture coding in order to improve a quality of an image. Split-and-merge method was employed for a segmentation. In the texture coding, a linear predictive coding(LPC), along with approximation technique based on a two-dimensional polynomial function was used to encode texture components. Depending on a size of region and a mean square error between an original and a reconstructed image, appropriate texture coding techniques were determined. A computer simulation on natural images indicates that an acceptable image quality at a compression ratio as high as 15-25 could be obtained. In comparison with a discrete cosine transform coding technique, which is the most typical coding technique in the first-generation coding, the proposed scheme leads to a better quality at compression ratio higher than 15-20.

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The Evaluation of Texture Image and Preference according to the Structural Characteristics of Silk Fabric (견직물의 구조적 특성에 따른 질감이미지와 선호도 평가)

  • Kim, Hee-Sook;Na, Mi-Hee
    • Korean Journal of Human Ecology
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    • v.18 no.1
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    • pp.137-143
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    • 2009
  • The purpose of this study is to examine the evaluation of texture image and preference according to the structural characteristics of silk fabric, and to analyze the effects of texture image and sensibility on the preference. 53 female subjects evaluated fabric image and sensibility of 17 specimens of white silk fabrics sold on the market with semantic differential scale. The data were analyzed through factor analysis, Pearson correlational coefficient and t-test using SPSS win 13.0. For the evaluation, structural characteristics such as fiber contents, weave type, weight and thickness were analyzed. Factor analysis showed that sensibilities were classified into 3 categories; 'surface property', 'weight', 'flexibility'. Fabric images were classified into 2 categories; 'elegance' and 'naturalness'. Statistically significant differences of structural characteristics on the texture image were observed. Weave type affected 'surface property' and fiber contents affected' flexibility'. Weight and weave type affected' elegance', too. The significant factors affecting preference were fabric image of 'elegance' and structural characteristics of 'weave type'. The results of this study showed that the most preferred silk fabric is smooth and soft satin weaved fabric with texture image of 'elegance'.

An Image Synthesis Technique Based on the Pyramidal Structure and MAP Estimation Technique (계층적 Pyramid구조와 MAP 추정 기법을 이용한 Texture 영상 합성 기법)

  • 정석윤;이상욱
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.8
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    • pp.1238-1246
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    • 1989
  • In this paper, a texture synthesis technique based on the NCAR(non-causal auto-regressive) model and the pyramid structure is proposed. In order to estimate the NCAR model parameters accurately from a noisy texture, the MAP(maximum a posteriori) estimation technique is also employed. In our approach, since the input texture is decomposed into the Laplacian oyramid planes first and then the NCAR model is applied to each plane, we are able to obtain a good synthesized texture even if the texture exhibits some non-random local structure or non-homogenity. The usrfulness of the proposed method is demonstrated with seveal real textures in the Brodatz album. Finally, the 2-dimensional MAP estimation technique can be used to the image restoration for noisy images as well as a texture image synthesis.

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Texture synthesis for model-based coding

  • Sohn, Young-Wook;Kim, In-Kwon;Park, Rae-Hong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1996.06b
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    • pp.23-28
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    • 1996
  • Model-based coding is one of several approaches to very low bit rate image coding and it can be used in many applications such as image creation and virtual reality. However, its analysis and synthesis processes remain difficult, especially in the sense that the resulting synthesized image reveals some degradation in detailed facial components such as furrows around eyes and mouth. To solve the problem, a large number of methods have been proposed and the texture update method is one of them. In this paper, we investigate texture synthesis for model-based coding. In the update process of the proposed texture synthesis algorithm, texture information is stored in a memory and the decoder reuses it. With this method, the transmission bit rate for texture data can be reduced compared with the conventional method updating texture periodically.

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A Synthetic Method for Generating Texture Patterns Similar to a Selected Original Texture Image

  • Shinji, Ohyama;Hong, Keum-Shik
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.35.5-35
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    • 2001
  • The purpose of the study is to develop a synthetic method for generating arbitrary number of not the same but similar texture images. The method includes processes to extract basic shape elements from texture images originating in actual objects, to select them to reappear the image features and to arrange them in a image plane. The authors have already proposed the shape-pass type filter bank assuming that the sensual impression mainly depends on minute shapes existing in the texture images. By use of nine basic shape elements, namely black/white-roof, black/white-line, black/white-snake, black/white-pepper, and cliff, natural texture images originating in actual objects have been characterized by feature vectors in a nine dimensional space. To generate arbitrary number of similar texture images, minute shape pieces ...

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Effect of the Drapability and the Texture Image on the Purchase Preference of Blouse Fabrics (블라우스용 소재의 드레이프성과 질감이미지가 구매선호도에 미치는 영향)

  • Kim, Yeo-Won;Pan, Hong-Yu;Na, Mi-Hee;Choi, Jong-Myoung
    • Korean Journal of Human Ecology
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    • v.20 no.5
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    • pp.1025-1034
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    • 2011
  • The purpose of this study was to examine the evaluation of fabric characteristics on the drapability, texture image and preference of blouse fabrics, and to analyze the effects of the texture image, objective and subjective drapability on the preference. As specimen, silk and polyester fabrics were collected. 52 female subjects evaluated 16 specimens with semantic differential scale of 18 fabric image and 20 sensibility. Data were analyzed through factor analysis, pearson correlational coefficient using spss win 12.0. For the evaluation, structural characteristics such as fiber contents, weave type, weight and thickness were analyzed. The results were as follows: The evaluation results of objective and subjective drapability showed differences. Sensory image factors of blouse fabrics were 'surface smoothness', 'elasticity', 'weight' and 'flexibility'. Sensibility image factors were 'elegance', 'classic', 'characteristic' and 'mannish'. 'Elegance', 'classic' and 'characteristic' of sensibility images showed high correlation with 'surface smoothness' and 'elasticity' of sensory image, also 'mannish' of sensibility image showed significant correlation with 'weight' of sensory image. The significant fabric characteristics affecting objective drapability were density, weight, thickness. The significant texture image factors affecting objective drapability were 'weight', 'flexibility' of sensory image and 'elegance' of sensibility image. On the other hand, the significant factors affecting subjective drapability were thickness of fabric characteristics and 'elegance', 'characteristic', 'mannish' of sensibility images. 'Elegance', 'characteristic' and 'classic' of sensibility image, 'elasticity' of sensory image and subjective drapability affected on the purchase preference.

A Study on the Facial Image Synthesis Using Texture Mapping and Shading Effect (명암효과와 질감매핑을 이용한 얼굴영상 합성에 관한 연구)

  • 김상현;정성환;김신환;김남철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.7
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    • pp.913-921
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    • 1993
  • Texture mapping is mostly used as an image synthesis method in the model-based coding system. An image synthesis using this method uses only the texture information of a front face-view. Therefore, when the model is rotated, texture mapping may produce an awkward image in point of shading. In this paper. a new texture mapping method considering shading effect is studied, and also the ear's wireframe and changes of hair are suplemented for the relation. The experimental results show that the proposed method yields the synthesized images with reasonably natural quality.

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Video image retrieval on the basis of subregional co-occurrence matrix texture features and normalised correlation (PIM 기반 국부적 Co-occurrence 행렬 및 normalised correlation를 이용한 효율적 비디오 검색 방법)

  • 김규헌;정세윤;전병태;이재연;배영래
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.601-604
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    • 1999
  • This Paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore. this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using Picture Information Measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggest six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to a various images and produces competitive results.

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Fractal coding of Textural Images (텍스처 영상의 프락탈 코딩)

  • Jang, Jong-Whan
    • The Journal of Natural Sciences
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    • v.8 no.2
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    • pp.77-82
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    • 1996
  • New very low bit rate segmentation image coding technique is proposed by segmenting image into textually homogeneous regions. Regions are classified into on of three perceptually distinct texture classes (perceived constant intensity (class I), smooth texture (class II), and rough texture (class III) using the human Visual System (HVS) and the fractals. To design very low bit rate image coder, it is very important to determine nonoverlap and overlap segmentation method for each texture class. Good quality reconstructed images are obtained with about 0.10 to 0.21 bit per pixel (bpp) for many different types of imagery.

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