• 제목/요약/키워드: Modified Image Method

검색결과 658건 처리시간 0.03초

A Study on Wavelet-based Image Denoising Using a Modified Adaptive Thresholding Method

  • Yinyu, Gao;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • 제10권1호
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    • pp.45-52
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    • 2012
  • Thedenoising of a natural image corrupted by Gaussian noise is a long established problem in signal or image processing. Today the research is focus on the wavelet domain, especially using the wavelet threshold method. In this paper, a waveletbased image denoising modified adaptive thresholding method is proposed. The proposed method computes thethreshold adaptively based on the scale level and adaptively estimates wavelet coefficients by using a modified thresholding function that considers the dependency between the parent coefficient and child coefficient and the soft thresholding function at different scales. Experimental results show that the proposed method provides high peak signal-to-noise ratio results and preserves the detailed information of the original image well, resulting in a superior quality image.

변형된 칼라 코렐로그램을 이용한 영상검색 (Image Retrieval using Modified Color Correlogram)

  • 안명석;조석제
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제29권12호
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    • pp.940-946
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    • 2002
  • 본 논문에서는 변형된 칼라 코렐로그램(Color Correlogram)을 이용한 영상검색 방법을 제안한다. 제안한 방법은 영상 내의 같은 칼라를 가지는 영역의 크기 변화에 강인하게 영상을 검색하기 위해, 영상에서 얻어진 칼라 코렐로그램의 오토-코렐로그램(auto-correlogram)과 크로스-코렐로그램(cross-correlogram) 영역을 각각 정규화하여 변형된 칼라 코렐로그램을 얻는다. 그리고 영상검색을 위한 유사도 측정시, 오토-코렐로그램에 가중치를 크로스-코렐로그램 영역보다 작게 준다. 제안한 방법은 칼라 코렐로그램의 정보를 효과적으로 사용함으로써, 영상검색 성능을 높일 수 있다. 실험을 통해 제안한 방법이 기존의 칼라 코렐로그램을 이용한 방법보다 효과적으로 영상을 검색할 수 있음을 확인하였다.

Modified Phillips-Tikhonov regularization for plasma image reconstruction with modified Laplacian matrix

  • 장시원;이승헌;최원호
    • 한국진공학회:학술대회논문집
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    • 한국진공학회 2009년도 제38회 동계학술대회 초록집
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    • pp.472-472
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    • 2010
  • The tomography has played a key role in tokamak plasma diagnostics for image reconstruction. The Phillips-Tikhonov (P-T) regularization method was attempted in this work to reconstruct cross-sectional phantom images of the plasma by minimizing the gradient between adjacent pixel data. Recent studies about the comparison of the several tomographic reconstruction methods showed that the P-T method produced more accurate results. We have studied existing Laplacian matrix used in Phillips-Tikhonov regularization method and developed modified Laplacian matrix (Modified L). The comparison of the reconstruction result by the modified L and existing L showed that modified L produced more accurate result. The difference was significantly pronounced when a portion of plasma was reconstructed. These results can be utilized in the Edge Plasma diagnostics; especially in divertor diagnostics on tokamak a large impact is expected. In addition, accurate reconstruction results from received data in only one direction were confirmed through phantom test by using P-T method with modified L. These results can be applied to the tangentially viewing pin-hole camera diagnostics on tokamak.

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A New Method of Remote Sensing Image Fusion Based on Modified Kohonen Networks

  • Shuhe, Zhao;Xiuwan, Chen;Junfeng, Chen;Yinghai, Ke
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1337-1339
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    • 2003
  • In this article, a new remote sensing image fusion model based on modified Kohonen networks is given. And a new fusion rule based on modified voting rule was established. Select Shaoxing City as the study site, located at Zhejiang Province, P.R.China. The fusion experiment between Landsat TM data (30m) and IRS-C Pan data (5.8m) was performed using the given fusion method. The fusion results show that the new method can gain better result in apply ing to the lower hill area, and the whole classification accuracy was 10% higher than the basic Kohonen method. The confusion between the woodlands and the waterbodies was also diminished.

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STABLE AUTONOMOUS DRIVING METHOD USING MODIFIED OTSU ALGORITHM

  • Lee, D.E.;Yoo, S.H.;Kim, Y.B.
    • International Journal of Automotive Technology
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    • 제7권2호
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    • pp.227-235
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    • 2006
  • In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

A NUMERICAL METHOD FOR THE MODIFIED VECTOR-VALUED ALLEN-CAHN PHASE-FIELD MODEL AND ITS APPLICATION TO MULTIPHASE IMAGE SEGMENTATION

  • Lee, Hyun Geun;Lee, June-Yub
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제18권1호
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    • pp.27-41
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    • 2014
  • In this paper, we present an efficient numerical method for multiphase image segmentation using a multiphase-field model. The method combines the vector-valued Allen-Cahn phase-field equation with initial data fitting terms containing prescribed interface width and fidelity constants. An efficient numerical solution is achieved using the recently developed hybrid operator splitting method for the vector-valued Allen-Cahn phase-field equation. We split the modified vector-valued Allen-Cahn equation into a nonlinear equation and a linear diffusion equation with a source term. The linear diffusion equation is discretized using an implicit scheme and the resulting implicit discrete system of equations is solved by a multigrid method. The nonlinear equation is solved semi-analytically using a closed-form solution. And by treating the source term of the linear diffusion equation explicitly, we solve the modified vector-valued Allen-Cahn equation in a decoupled way. By decoupling the governing equation, we can speed up the segmentation process with multiple phases. We perform some characteristic numerical experiments for multiphase image segmentation.

3D Image Correlator using Computational Integral Imaging Reconstruction Based on Modified Convolution Property of Periodic Functions

  • Jang, Jae-Young;Shin, Donghak;Lee, Byung-Gook;Hong, Suk-Pyo;Kim, Eun-Soo
    • Journal of the Optical Society of Korea
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    • 제18권4호
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    • pp.388-394
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    • 2014
  • In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

Image Analysis of the Luster of Fabrics with Modified Cross-section Fibers

  • Shin Kyung In;Kim Seong Hun;Kim Jong Jun
    • Fibers and Polymers
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    • 제6권1호
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    • pp.82-88
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    • 2005
  • We have investigated the luster of modified cross-sectional fiber fabrics as one of the essential quality estimates for clothing development. We have confirmed an objective evaluation method, and have determined the experimental luster char­acteristics of modified cross-section fibers. The cross-section of the fibers in a fabric affects the appearance of a textile. We used the image analysis method to investigate the luster to determine the critical factors influencing the appearance of modi­fied cross-section fiber fabrics. For similarly structured textiles in a component fabric, clear differences were observed in the fabric weave, density, percentage, and total area of blobs, which is image region. Color played a decisive role in the luster of the textiles, and luster was not significantly influenced by the modified cross-section fabric weave. In addition, the degree of luster did not increase in the order plain to twill to satin for modified cross-sectional fiber fabrics. All the split-type microfi­bers exhibited higher numerical luster values (percentage of pixels, and number and total area of blobs) than sea-island microfibers did. The degree of luster of the modified cross-sectional fiber fabrics was not high at specular reflection angles.

영상검색에서의 다중 피쳐 결합을 위한 변형된 보다 카운트 방법 (Modified Borda Count Method for Combining Multiple Features of Image Retrieval)

  • 정세윤;김규헌;전병태;이재연;배영래
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 추계종합학술대회 논문집
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    • pp.593-596
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    • 1999
  • In this paper, we propose an image retrieval system using the MBCM(Modified Borda Count method) in CME(Combining Multiple Experts). It combines color-, shape- and texture-based retrieval sub-systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment, our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

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수정된 디지털 이미지에서 기하학적 변형 및 필터링 변형 영역을 식별하는 기법 (Identification Method of Geometric and Filtering Change Regions in Modified Digital Images)

  • 황민구;조병주;하동환
    • 한국멀티미디어학회논문지
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    • 제15권11호
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    • pp.1292-1304
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    • 2012
  • 최근에 디지털 이미지는 광고주나 이미지 편집자들에 의해 극단적으로 수정되는 경우가 많다. 또한 일반인들도 간단한 편집 프로그램을 통해 원본 이미지를 수정함으로써 사진을 조작하곤 한다. 본 논문에서는 이러한 문제를 해결하기 위해서 수정된 이미지에 대한 식별 및 분석 방법을 제안하고자 한다. 수정 이미지 분석에는 크게 기하학적 변형(geometric changes)과 필터링 변형(filtering change)으로 나누었다. 이러한 변형에는 항상 보간법을 기반으로 한 알고리즘을 내포하고 있기 때문에 보간의 흔적을 분석할 수 있는 알고리즘을 제안하였다. 그 방법으로 minimum 필터와 laplacian 연산 그리고 maximum 필터를 이용한 보간 검출 맵을 구현하였으며, 실제로 수정된 이미지에 제안하는 알고리즘을 적용하여 변형된 흔적을 검출 맵을 통해 분석할 수 있었다.