• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.36-45
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• 2006

Three-dimensional (3-D) texture coordinates mean the position information of torture segments that are mapped into polygons in a 3-D mesh model. In order to compress texture coordinates, previous works reused the same linear predictor that had already been employed to code geometry data. However, the previous approaches could not carry out linear prediction efficiently since texture coordinates were discontinuous along a coding order. Especially, discontinuities of texture coordinates became more serious in the 3-D mesh model including a non-atlas texture. In this paper, we propose a new scheme to code 3-D texture coordinates using as a texture image rearrangement. The proposed coding scheme first extracts texture segments from a texture. Then, we rearrange the texture segments consecutively along the coding order, and apply a linear prediction to compress texture coordinates. Since the proposed scheme minimizes discontinuities of texture coordinates, we can improve coding efficiency of texture coordinates. Experiment results show that the proposed scheme outperforms the MPEG-4 3DMC standard in terms of coding efficiency.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.237-248
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• 2010

When scenes in the real world are perceived for the purpose of computer/robot vision fields, there are great deals of texture based patterns in them. This paper introduces a texture feature representation on a coordinate system in which many different patterns can be represented with a mathematical model (Gabor function). The representation of texture features of each pattern on the coordinate system results in the high performance/competence of texture pattern classification. A decision tree algorithm is used to classify pattern data represented on the proposed coordinate system. The experimental results for the texture pattern classification show that the proposed method is better than previous researches.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.748-750
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• 2005

본 논문은 오목한 물체의 그림자 표현이 가능한 그림자 텍스처를 생성하기 위해, 기존의 그림자 맵 (shadow MaP) 방법으로 그림자 정보를 생성하고 아틀라스 텍스처 (atlas texture)에 저장하는 방법을 제안한다. 기존 그림자 텍스처 방법은 그림자 정보를 이미지 텍스처에 저장하므로 그래픽스 하드웨어의 색상 처리 기능을 사용하여 고품질의 그림자를 효율적으로 표현하는 장점이 있지만 오목한 물체의 그림자를 표현하지 못하고 그림자 텍스처 생성에 많은 시간이 소요되는 문제점을 가지고 있다. 실험 결과, 새로운 방법은 그림자 텍스처의 문제점을 해결하고 고품질의 그림자를 표현하는 것을 알 수 있다.

• Digital Contents
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• no.12 s.127
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• pp.151-153
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• 2003

프로시저 텍스처(Procedural Textures)는 게임업계의 많은 아티스트에게 악명이 높다. 이것은 일부 사용하기가 어렵기 때문이다. 프로시저 텍스처는 페인팅보다는 프로그래밍에 가깝다. 특히 합성 텍스처에서 잘 알려진 렌더만 (Renderman)은 완전히 변형된 언어이며 패키지가 지원하는 다양한 프론트 엔드는 거의 C++ 수준 매뉴얼처럼 미스테리하다. 또한 프로시저는 아티스트 측면에서 많은 의혹을 불러일으킨다. 진부하고 거의 불가피한 베이니 마블과 프랙탈 잡음은 파워포인트 클립아트의 CG 대응부다. 이러한 구조를 이용할 때 왜 프로시저 텍스처에 컬럼을 할애했는지 궁금할 수도 있을 것이다. 이번 호에는 프로시저 텍스처를 살펴봐야 하는 세 가지 이유를 정리했다.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.287-295
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• 2006

This paper compares two different approaches based on wavelet and Gabor decomposition towards representing the texture of an arbitrary region. The Gabor-domain mean and standard deviation combination is considered to be best in representing the texture of rectangular regions. However, texture representation of arbitrary regions would enable generalized object-based image retrieval and other applications in the future. In this study, we have found that the wavelet features perform better than the Gabor features in representing the texture of arbitrary regions. Particularly, the wavelet-domain standard deviation and entropy combination results in the best retrieval accuracy. Based on our experiment with texture image sets, we present and compare tile retrieval accuracy of multiple wavelet and Gabor feature combinations.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1550-1555
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• 2004

Shadows increase the visual realism of computer-generated images and they are good hint for spatial relationships between objects. Previous methods to produce a shadow texture for an object are to render all objects between the object and light source. Consequently entire time for generating shadow textures between all objects is Ο(Ν$^2$), where Ν is the number of objects. We propose a novel shadow texture generation method with constant processing time for each object using shadow depth buffet. In addition, we also present method to achieve further speed-up using temporal coherence. If the transition between dynamic and static state is not frequent, depth values of static objects does not vary significantly. So we can reuse the depth value for static objects and render only dynamic objects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.201-205
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• 2020

The structural texture is defined as a form which a texel is regularly repeated in the texture. Structural texture analysis/recognition has various industrial applications, such as automatic inspection of textiles, automatic testing of metal surfaces, and automatic analysis of micro images. In this paper, we propose a Convolution Neural Network (CNN) based system for structural texture analysis. The proposed method learns texles, which are components of textures to be classified. Then, this trained CNN recognizes a structural texture using a partial image obtained from input texture. The experiment shows the superiority of the proposed system.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.10-18
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• 2012

Automatic smoke detection systems using a surveillance camera requires a reliable smoke detection method. When an image sequence is captured from smoke spreading over in the air, not only has each smoke image frame a special texture, called static texture, but the difference between two smoke image frames also has a peculiar texture, called dynamic texture. Even though an object has a static texture similar to that of the smoke, its dynamic texture cannot be similar to that of the smoke if its movement differs from the diffraction action of the smoke. This paper presents a reliable smoke detection method using these two textures. The proposed method first detects change regions using accumulated frame difference, and then picks out smoke regions using Haralick features extracted from two textures.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.839-841
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• 2000

텍스처 정보는 정지 영상 뿐 아니라 동영상 분석에서도 많은 정보를 제공한다. 이러한 텍스처 정보를 동영상의 움직임 분류에 사용하여 기존의 색, 색영역의 배치 정보, 기준 형상, 명도 텍스처 등을 기본 탐색 키로 삼는 동영상 검색 시스템에 텍스처 특성을 움직임 정보에 적용하여 저 수준 정보에서 움직임 정보가 직접적으로 추출될 수 있음을 보였다. 이 방법의 장점은 배경 소거, 오브젝트 추출 및 추적, 참조 곡선 탐색 등 많은 계산량을 요구하는 연산들이 없이도 움직임 정보를 압축 동영상에서 추출할 수 있다는 것이다. 또한 동영상은 데이터의 양이 매우 크기 때문에 압축되어 있는 것이 필수인데 본 연구에서는 웨이브릿으로 압축되어 있는 동영상에서 움직임 정보가 고주파 부분에 집중되어 있는 점을 이용하여 역변환을 거치지 않고 직접 템포럴 텍스처를 생성하였다. 따라서 계산 속도를 향상시켰으며 계산 과정도 행렬 연산을 기본으로 수행하여 계산 과정을 간단하게 하였다.

• 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.