• Title/Summary/Keyword: Visual texture

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Adaptive Watermark Detection Algorithm Using Perceptual Model and Statistical Decision Method Based on Multiwavelet Transform

  • Hwang Eui-Chang;Kim Dong Kyue;Moon Kwang-Seok;Kwon Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.8 no.6
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    • pp.783-789
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    • 2005
  • This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

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Development of a Luxuriousness Model for Wall Paper Design based on Visual and Tactile Characteristics (벽지의 디자인 요소 및 감성적 특성에 의한 고급감 모델 개발)

  • Ban Sang-U;Lee Ju-Hwan;Kim In-Gi;Lee Cheol;Yun Myeong-Hwan
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.193-197
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    • 2006
  • 본 연구는 감성 공학적 접근법을 사용하여, 벽지의 디자인 요소와 소비자의 감성과의 관계를 정량적으로 규명하는 것을 목표로 한다. 문헌조사, 인터뷰 전문가 의견 등을 종합하여, 총 13개의 주관적 감성 변수(6개의 시각적 변수, 7개의 촉각적 변수) 와 4개의 벽지 디자인 요소(color, texture pattern, embossing depth, gloss)들이 추출되었으며, 최종 목표 감성은 '고급감'으로 정하였다. 9점 척도와 100점 척도으로 구성된 설문지를 통하여, 28개의 샘플 벽지에 대해서 30명의 목표 고객들을 대상으로 감성 평가 실험을 실시하였고, 주성분 회귀 분석, 수량화 이론 등을 이용한 분석을 통하여, 소비자의 감성과 디자인 요소와의 관계를 정량적으로 분석했으며, 고급감을 향상시킬 수 있는 감성 변수 조합과 디자인 요소 조합을 규명하였다.

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Robust Watermarking toward Compression Attack in Color Image (압축공격에 강인한 칼라영상의 워터마킹)

  • Kim Yoon-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.3
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    • pp.616-621
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    • 2005
  • In this paper. digital watermarking algorithm based on human visual system and transform domain is presented. Firstly, original image is separated into RGB thannels, watermark is embedded into the coefficients of DCT so as to consider a contrast sensitivity and texture degrees. In preprocessing, DCT domain based transform is involved and binary image of visually recognizable patterns is utilized as a watermark. Consequently, experimental results showed that proposed algorithm is robust and imperceptibility such destruction attack as JPEG compression.

Crop Field Extraction Method using NDVI and Texture from Landsat TM Images

  • Shibasaki, Ryosuke;Suzaki, Junichi
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.159-162
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    • 1998
  • Land cover and land use classification on a huge scale, e.g. national or continental scale, has become more and more important because environmental researches need land cover: And land use data on such scales. We developed a crop field extraction method, which is one of the steps in our land cover classification system for a huge area. Firstly, a crop field model is defined to characterize "crop field" in terms of NDVI value and textual information Textual information is represented by the density of straight lines which are extracted by wavelet transform. Secondly, candidates of NDVI threshold value are determined by "scale-space filtering" method. The most appropriate threshold value among the candidates is determined by evaluating the line density of the area extracted by the threshold value. Finally, the crop field is extracted by applying level slicing to Landsat TM image with the threshold value determined above. The experiment demonstrates that the extracted area by this method coincides very well with the one extracted by visual interpretation.

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TangibleScreen : Enhancing Interactivity through Object-centric Projection (TangibleScreen 객체중심 프로젝션을 통한 상호작용성 향상)

  • Shin, Seon-Hyung;Kim, Joung-Hyun Gerard
    • Journal of the Korea Computer Graphics Society
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    • v.9 no.1
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    • pp.19-27
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    • 2003
  • Most interaction schemes in virtual environment are indirect in one way or another. ln particular, without a haptic device (which introduces its own problems due to its cumbersomeness), users must rely on visual (or/and aural) feedback, and can not directly appreciate the 3Dness of the interaction object even with stereoscopy. This causes a drop in object presence because people are used to, for instance, observing objects in one's hand, rotating and manipulating them with physical contact. To alleviate this problem, this paper proposes a hand-held cubic screen, named TangibleScreen, on which the appearance of the target interaction object is projected. We choose the Relief Texture Mapping as the rendering method to correctly generate the viewer dependent textures to be projected on the non-planar surfaces of the TangibleScreen.

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2D and 3D Visual Information Measurement in terms of Entropy (엔트로피 관점에서 2D 와 3D 동영상의 시각적 정보량 측정방법)

  • Ahn, Sewoong;Lee, Sanghoon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2015.11a
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    • pp.8-10
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    • 2015
  • 최근 2D 와 3D 콘텐츠의 급격한 수요 증가로 인하여 2D 와 3D 공간에서 사람이 인지하는 물체의 시각적 정보량을 정량화할 필요성이 대두되었다. 본 논문에서는 정보이론에 기초하여 엔트로피 관점에서 2D 와 3D 영상의 시각적 정보량을 측정하는 방법을 제시한다. 시각적 정보량을 측정할 때, 기존의 연구에서는 고려되지 않았던 집중영역(saliency), 시각세포의 불균형으로 인한 주변영역 흐림현상인 포비에이션(foveation), 양안합성(binocular fusion)등 인간의 시각적 특성을 반영하였다는 점에서 기존의 연구들과 차이를 둔다. 2D 콘텐츠의 시각적 엔트로피는 단안시에 근거한 질감(texture) 엔트로피와 깊이 엔트로피로 구성되어 있다. 그리고 3D 콘텐츠의 시각적 엔트로피는 2D 에서의 시각적 엔트로피와 양안시에 의한 깊이 엔트로피를 포함한다. 본 논문의 시각적 엔트로피는 2D 와 3D 영상의 시각적 피로도를 측정할 때 사용될 수 있다.

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A Study on Composition Factor and Special Qualities of Design about Korean Clothing Image (한국적 의복이미지의 구성요인과 디자인 특성)

  • 김희정;이경희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.21 no.3
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    • pp.589-599
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    • 1997
  • The purpose of this study was to investigate compostion factor and special qualities of design about Korean clothing image. The 72 samples were obtained from domestic fashion magazines. The questionnaire, which was composed 23 semantic diffrential bi-polar scales, was distributed to 50 female students majoring in Clothing and Textiles. The data were analyzed through factor analysis, anova, scheffe's test, clust analysis. The results were as follows; 1) Through factor analysis about Korean clothing image, 5 factors were identified; elegance, simplicity, femininity, tradition, looseness. 2) By cluster analysis, 3 clusters were determined according to Korean clothing image. Special qualities of design about Korean clothing image showed that there were lots of H silhouette in clothing form, related harmony in color harmony, somewhat rough and crude in texture and simple design in decoration. Top was more or less fit and bottom was found somewhat exaggerated tendency in fitness. 3) As a result of the visual evaluation about Korean clothing image, there were significant differences in all factors.

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Enhancing Single Thermal Image Depth Estimation via Multi-Channel Remapping for Thermal Images (열화상 이미지 다중 채널 재매핑을 통한 단일 열화상 이미지 깊이 추정 향상)

  • Kim, Jeongyun;Jeon, Myung-Hwan;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.17 no.3
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    • pp.314-321
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    • 2022
  • Depth information used in SLAM and visual odometry is essential in robotics. Depth information often obtained from sensors or learned by networks. While learning-based methods have gained popularity, they are mostly limited to RGB images. However, the limitation of RGB images occurs in visually derailed environments. Thermal cameras are in the spotlight as a way to solve these problems. Unlike RGB images, thermal images reliably perceive the environment regardless of the illumination variance but show lacking contrast and texture. This low contrast in the thermal image prohibits an algorithm from effectively learning the underlying scene details. To tackle these challenges, we propose multi-channel remapping for contrast. Our method allows a learning-based depth prediction model to have an accurate depth prediction even in low light conditions. We validate the feasibility and show that our multi-channel remapping method outperforms the existing methods both visually and quantitatively over our dataset.

COLORNET: Importance of Color Spaces in Content based Image Retrieval

  • Judy Gateri;Richard Rimiru;Micheal Kimwele
    • International Journal of Computer Science & Network Security
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    • v.23 no.5
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    • pp.33-40
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    • 2023
  • The mainstay of current image recovery frameworks is Content-Based Image Retrieval (CBIR). The most distinctive retrieval method involves the submission of an image query, after which the system extracts visual characteristics such as shape, color, and texture from the images. Most of the techniques use RGB color space to extract and classify images as it is the default color space of the images when those techniques fail to change the color space of the images. To determine the most effective color space for retrieving images, this research discusses the transformation of RGB to different color spaces, feature extraction, and usage of Convolutional Neural Networks for retrieval.

Using Radon Transform for Image Retrieval (영상 검색을 위한 Radon 변형의 이용)

  • Seo, Jeong-Man
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.6
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    • pp.65-71
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    • 2009
  • The basic features in the indexing and retrieval of the image is used color, shape, and texture in traditional image retrieval method. We do not use these features and offers a new way. For content-based video indexing and retrieval, visual features used to measure the similarity of the geometric method is presented. This method is called the Radon transform. Without separation, this method is calculated based on the geometric distribution of image. In the experiment has a very good search results.