• 제목/요약/키워드: Image Representation

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영화의 시간성 표현을 위한 기호학적 모델의 제언 -들뢰즈 "운동-이미지"의 기호화 과정을 중심으로- (Semiotic Approach to the Representation Process of Time in Cinema)

  • 김병선
    • 한국언론정보학보
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    • 제26권
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    • pp.7-44
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    • 2004
  • 이 논문은 영화에서의 시간성 표현 과정에 대한 기호학적 모델을 구성하기 위해 작성된 것이다. 연구자는 영화의 시간성 표현과 관련된 기존 서사 이론의 한계를 지적하고 이에 대한 대안으로서 들뢰즈(Gille Deleuze) 영화 철학(philosophy of cinema)의 적절성을 논의했다. 들뢰즈 영화 철학은 퍼스(Charles S. Peirce)의 삼원론적 기호학을 영화에 가장 잘 적용시킨 것으로 평가될 수 있는데, 이에 따라 연구자는 우선 영화를 구성하는 기호학적 최소 단위로서의 "운동아미지" 개념을 논의한 다음 이를 기반으로 고전적 서사 영화(classic narrative cinema)와 현대 영화(modern cinema)에서 나타나는 두 가지 서로 다른 시간성 표현의 기호화 과정을 비교했다. 즉, 고전적 서사 영화에서는 "정상적인 운동이미지"가 "간접적 시간 표현"과 "이야기-서사"라는 해석체를 구성하는 기호화 과정을 거치는 반면, 현대 영화에서는 "비정상적 운동이미지"가 "직접적시간 표현"과 "시간-이미지"라는 해석차를 구성하는 또 다른 기호화 과정을 거치는 것으로 보았다. 현대 영화의 기호학 과정에서 출현하고 있는 이와 같은 "시간-이미지"는 영화와 현실 사이에 놓여진 "시간"이라는 철학적 대상을 통찰하게 만들고 기존의 가치관과 이데올로기의 상투성을 극복할 수 있게 만든다. 이러한 맥락에서 "비정상적인 운동이미지"룰 만들어 내는 현대적 영상 제작 작업은 단지 특이하고 새로운 영화적 표현을 구성하는 데에만 그치는 것이 아니라, 시간을 주요한 사유의 대상으로 취하고 새로운 철학적 사유를 하게 만드는 보다 근원적인 성격을 가질 수 있게 되는 것이다.

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자연 화상에서 점묘화풍 화상으로의 자동생성 (Automatic Generation of Pointillist Representation-like Image from Natural Image)

  • 도현숙;조평동;최영진
    • 한국정보처리학회논문지
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    • 제2권1호
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    • pp.130-136
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    • 1995
  • 본 논문에서는 자연 화상을 입력하여 점묘화풍 화상으로 자동 생성하기 위한 방 법에 대해 논한다. 점묘화풍 화상을 생성하기 위하여 두 가지 기법을 고려하였다. 첫째는 입력된 화상을 해석하여 화상내의 각 화소들의 그레디언트 벡타를 구하고 붓 이 터치되는 위치를 결정하는데 사용한다. 둘째는 색의 표현 인데, 화상 내의 RGB 성분을 이용하여 명도, 채도 등의 변환을 통해 점묘화풍의 선명하고 밝은 느낌을 나타 내도록 하였다. 이 논문에서는 컴퓨터 그래픽스 기술에 화상 처리를 접합시킨 실험적 인 방법을 제시하였으며, 그 방법에 의해 생성된 몇 개의 점묘화풍 화상을 예시하였다.

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자유시점 TV를 위한 다시점 비디오의 계층적 깊이 영상 표현과 H.264 부호화 (Layered Depth Image Representation And H.264 Encoding of Multi-view video For Free viewpoint TV)

  • 신종홍
    • 디지털산업정보학회논문지
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    • 제7권2호
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    • pp.91-100
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    • 2011
  • Free viewpoint TV can provide multi-angle view point images for viewer needs. In the real world, But all angle view point images can not be captured by camera. Only a few any angle view point images are captured by each camera. Group of the captured images is called multi-view image. Therefore free viewpoint TV wants to production of virtual sub angle view point images form captured any angle view point images. Interpolation methods are known of this problem general solution. To product interpolated view point image of correct angle need to depth image of multi-view image. Unfortunately, multi-view video including depth image is necessary to develop a new compression encoding technique for storage and transmission because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method using layered depth image representation and H.264/AVC video coding technology. In experimental results, confirmed high compression performance and good quality reconstructed image.

실내디자인 이미지 유형의 특성에 따른 표현어휘 연구 - 2008년도 국제박람회를 중심으로 - (A Study on the representation-language from image features of Interior Design - Focused on 2008 International Fair -)

  • 신동관;한영호
    • 한국실내디자인학회논문집
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    • 제17권6호
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    • pp.216-224
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    • 2008
  • The represented Design Language have to include design meaning by functions in Interior. It also is able to easy and quick to understand in conversation for the design proposal. In this study, 6 stages suggest for the basic forming image in Interior Design. Those are form, line, space, color, material and principles of design. And essential image language arranged by preceding research. The fundamental 6 elements of space are used for explanation with the minimum method to make consumer understand through some image. Image has the communication function as a visual conversation in Space Design. The purpose of using the image language is the exchange into communication by written visual image. In order to it is necessary to delivery correct meaning of Interior Design for the understand between consumer and designer for the suggestion through images. Therefore, making categories for representation-language from image features of interior design is a important research with the value to share the spatial pattern. It will be expected to add the spatial Image language by processing with new trend.

A novel hybrid method for robust infrared target detection

  • Wang, Xin;Xu, Lingling;Zhang, Yuzhen;Ning, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.5006-5022
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    • 2017
  • Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

An Edge Detection Method for Gray Scale Images Based on their Fuzzy System Representation

  • Moon, Byung-Soo;Lee, Hyun-Chul;Kim, Jang-Yeol
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.283-286
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    • 2001
  • Based on a fuzzy system representation of gray scale images, we derive an edge detection algorithm whose convolution kernel is different from the known kernels such as those of Roberts', Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3 3 kernel. We also show that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

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Sparse Representation based Two-dimensional Bar Code Image Super-resolution

  • Shen, Yiling;Liu, Ningzhong;Sun, Han
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권4호
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    • pp.2109-2123
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    • 2017
  • This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

Post-Processing for JPEG-Coded Image Deblocking via Sparse Representation and Adaptive Residual Threshold

  • Wang, Liping;Zhou, Xiao;Wang, Chengyou;Jiang, Baochen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권3호
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    • pp.1700-1721
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    • 2017
  • The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.

계층적 깊이 영상으로 표현된 다시점 비디오에 대한 H.264 부호화 기술 (H.264 Encoding Technique of Multi-view Video expressed by Layered Depth Image)

  • 신종홍;지인호
    • 한국인터넷방송통신학회논문지
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    • 제14권2호
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    • pp.43-51
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    • 2014
  • 깊이 영상을 고려한 다시점 비디오는 매우 많은 양의 데이터 때문에 저장과 전송을 위해서 새로운 부호화 압축 기술 개발이 요구된다. 계층적 깊이 영상은 다시점 비디오의 효과적인 표현방법이 된다. 이 방법은 다시점 칼라와 깊이 영상을 합성하는 데이터 구조를 만들어 준다. 이 새로운 콘텐츠를 효과적으로 압축하는 방법으로 3차원 워핑을 이용한 계층적 깊이 영상 표현과 비디오 압축 부호화를 적용하는 방법을 제안하였다. 이 논문은 계층적 영상 표현을 사용한 H.264/AVC 비디오 부호화 기술의 개선된 압축 방법을 제시하여 준다. 컴퓨터 모의시험으로 좋은 압축율과 좋은 성능의 회복 영상을 얻을 수 있음을 제시하였다.

Domain Adaptation Image Classification Based on Multi-sparse Representation

  • Zhang, Xu;Wang, Xiaofeng;Du, Yue;Qin, Xiaoyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권5호
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    • pp.2590-2606
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    • 2017
  • Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.