• 제목/요약/키워드: Complex images

검색결과 1,009건 처리시간 0.026초

Texture Image Fusion on Wavelet Scheme with Space Borne High Resolution Imagery: An Experimental Study

  • Yoo, Hee-Young;Lee , Ki-Won
    • 대한원격탐사학회지
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    • 제21권3호
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    • pp.243-252
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    • 2005
  • Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.

타원 모델링을 이용한 사람 머리 추적 시스템 구현 (Human head tracking system using the ellipse modeling)

  • 이명재;박동선;조재완;이용범
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.749-752
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    • 1998
  • Recognizing a human part becomes very important for applications which are based on the interaction between computers and their users. In this paper, we design and implement a system which recognizes and tracks a human head using a sequence of images. Difference images are used to easily extract feature vectors from images with very complex backgrounds. A human bhead is represented with an ellipse and recognized by searching for a maximum value from preprocessed gradient images. The method is developed by considering the fact that the tracking system should be real-time. The designed system not only shows an excellent performance for the normal up-right position of the head, but also for the cases of 360.deg. rotated head position, occluded images of heads, and tilted head positions.

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A Proposal for Processor for Improved Utilization of High resolution Satellite Images

  • Choi, Kyeong-Hwan;Kim, Sung-Jae;Jo, Yun-Won;Jo, Myung-Hee
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.211-214
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    • 2007
  • With the recent development of spatial information technology, the relative importance of satellite image contents has increased to about 62%, the techniques related to satellite images have improved, and their demand is gradually increasing. Accordingly, a standard processing method for the whole process of collection from satellites to distribution of satellite images is required in many countries for efficient distribution of images and improvement of their utilization. This study presents the processor standardization technique for the preprocessing of satellite images including geometric correction, orthorectification, color adjustment, interpolation for DEM (Digital Elevation Model) production, rearrangement, and image data management, which will standardize the subjective, complex process and improve their utilization by making it easy for general users to use them

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역전파 신경망을 이용한 동영상에서의 얼굴 검출 및 트래킹 (Face Detection Tracking in Sequential Images using Backpropagation)

  • 지승환;김용주;김정환;박민용
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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    • pp.124-127
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    • 1997
  • In this paper, we propose the new face detection and tracking angorithm in sequential images which have complex background. In order to apply face deteciton algorithm efficently, we convert the conventional RGB coordiantes into CIE coordonates and make the input images insensitive to luminace. And human face shapes and colors are learned using ueural network's backpropagation. For variable face size, we make mosaic size of input images vary and get the face location with various size through neural network. Besides, in sequential images, we suggest face motion tracking algorithm through image substraction processing and thresholding. At this time, for accurate face tracking, we use the face location of previous. image. Finally, we verify the real-time applicability of the proposed algorithm by the simple simulation.

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고분해능 투과전자현미경 연구에 의한 ${\gamma}$-Al2O3의 상 전산모사 (Compouter Image Simulation of ${\gamma}$-Al2O3 in High-Resolution Transimission Electron Microscopy)

  • 이정용
    • 한국세라믹학회지
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    • 제26권2호
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    • pp.276-288
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    • 1989
  • Interpretation of high-resolution transmission electron microscopy images of defects and complex structures such as found in ceramics generally requires matching of the images with compound image simulations for reliable interpretation. A transmission electron microscopy study of the aluminum oxide was carried out at high-resolution, so that the crystal structure of the aluminum oxide could be modelled on an atomic level. In conjunction with computer simulation comparisons, the images reveal directly the atomic structure of the oxide. Results show that comparison between experimental high-resolution electron microscopy images and simulated images leads to a one to one correspondence of the image to the atomic model of the aluminum oxide. The aluminum atoms are disordered in the octahedral sites and the tetrahedral sites in the spinel aluminum oxide.

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Transfer-learning-based classification of pathological brain magnetic resonance images

  • Serkan Savas;Cagri Damar
    • ETRI Journal
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    • 제46권2호
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    • pp.263-276
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    • 2024
  • Different diseases occur in the brain. For instance, hereditary and progressive diseases affect and degenerate the white matter. Although addressing, diagnosing, and treating complex abnormalities in the brain is challenging, different strategies have been presented with significant advances in medical research. With state-of-art developments in artificial intelligence, new techniques are being applied to brain magnetic resonance images. Deep learning has been recently used for the segmentation and classification of brain images. In this study, we classified normal and pathological brain images using pretrained deep models through transfer learning. The EfficientNet-B5 model reached the highest accuracy of 98.39% on real data, 91.96% on augmented data, and 100% on pathological data. To verify the reliability of the model, fivefold cross-validation and a two-tier cross-test were applied. The results suggest that the proposed method performs reasonably on the classification of brain magnetic resonance images.

로그 전력 스펙트럼을 이용한 초음파 영상에서의 장기인식 (Organ Recognition in Ultrasound images Using Log Power Spectrum)

  • 박수진;손재곤;김남철
    • 한국통신학회논문지
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    • 제28권9C호
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    • pp.876-883
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    • 2003
  • 본 논문에서는 초음파 영상에서 로그 전력 스펙트럼(log power spectrum)을 이용한 장기 인식 알고리듬을 제시한다. 제안한 알고리듬은 크게 특징추출과 특징분류의 두 단계로 구성된다. 특징추출에서는 이동불변의 성질을 가지는 로그 전력 스펙트럼을 이용하여 전처리를 수행한 입력 영상으로부터 장기 조직의 반향(echo of the tissue) 성분을 추출한다. 특징 분류에서는 마하라노비스(Mahalanobis) 거리를 사용하여 입력영상으로부터 추출한 특징벡터와 각 영상 부류의 평균벡터 사이의 유사도를 측정한다. 실제 초음파 영상에 대한 실험결과는 제안된 알고리듬이 전력 스펙트럼(power spectrum)과 유클리드(Euclid) 거리를 이용한 인식 알고리듬보다 최대 30% 향상된 인식률을, 또 가중 큐프런시(weighted quefrency) 복소 켑스트럼(complex cepstrum)을 이용한 알고리듬보다 10∼40% 향상된 인식률을 보여준다.

잡음에 강건한 주목 연산자의 구현과 효과적인 다중 물체 검출 (An Implementation of Noise-Tolerant Context-free Attention Operator and its Application to Efficient Multi-Object Detection)

  • 박창준;조상현;최흥문
    • 대한전자공학회논문지SP
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    • 제38권1호
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    • pp.89-96
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    • 2001
  • 본 논문에서는 잡음에 강건한 일반화 대칭 변환을 주목 연산자로 제안하고 이를 이용하여 크기와 형태가 다양한 물체들을 효과적으로 검출하였다. 기존의 주목 연산자와는 달리 두 화소의 명도변화의 크기와 대칭성뿐만 아니라 방사(radial)방향 명도변화의 수렴 및 발산을 누적 대칭도에 반영시킴으로써 명도변화 방향의 일관된 수렴이나 발산이 없는 잡음 영역에 의한 대칭 기여도가 누적되지 않도록 하였다. 따라서 제안한 주목 연산자를 사용하면 잡음이 많고 복잡한 배경으로부터 물체만을 쉽게 검출할 수 있도록 하였다. 다양한 합성영상(synthetic images)과 실영상(real images)에 대해 실험하여 잡음의 영향을 적게 받으며 효과적으로 다중 물체를 검출함을 확인하였다.

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Snake 모델을 이용한 다중 이동 객체 검출 및 추적 (Multiple Moving Objects Detection and Tracking Using Snake Model)

  • 우장명;김성동;최기호
    • 한국ITS학회 논문지
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    • 제2권2호
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    • pp.85-95
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    • 2003
  • 본 논문은 Snake 모델을 이용하여 동영상에서 주위 환경 변화에 적응 가능한 다중 이동 객체 추적 시스템을 제안하였다. Snake 모델은 배경이 복잡한 영상에 대해선 객체의 윤곽선을 정확히 표현하지 못하므로 영상분할 시 초기 위치에 따라 민감하게 영향을 받는다. 제안된 시스템은 프레임간의 차(difference)영상을 이용하여 배경영상을 획득하고, 픽셀의 인접성을 조사하여 객체를 분할하고 위치 특징 값을 구하며, 분할된 특징 값들을 Snake모델의 초기 위치 값으로 부여함으로써 초기 위치 값에 민감한 Snake 모델을 개선하였다 또한 본 시스템은 복잡한 배경 영상을 단순화하고, Snake를 이루는 각 정점들을 객체의 위치로 놓이게 함으로써 탐색 공간을 줄였다. 30fps로 저장된 AVI파일을 적용함으로써 다중 이동차량 추적 시스템으로의 응용 가능함을 보였다.

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DIGITAL WATERMARKING BASED ON COMPLEXITY OF BLOCK

  • Funahashi, Keita;Inazumi, Yasuhiro;Horita, Yuukou
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.678-683
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    • 2009
  • A lot of researches [1] have been conducted on digital watermark embedding in brightness. A prerequisite for the digital watermark is that the image quality does not change even if the volume of the embedded information increases. Generally, the noise on complex images is perceived than the noise on fiat images. Thus, we present a method for watermarking an image by embedding complex areas by priority. The proposed method has achieved higher image quality of digital watermarking compared to other method that do not take into consideration the complexity of blocks, although the PSNR of the proposed method is lower than for a method not based on block complexity.

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