• Title/Summary/Keyword: 화소패턴

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Classification of Scaled Textured Images Using Normalized Pattern Spectrum Based on Mathematical Morphology (형태학적 정규화 패턴 스펙트럼을 이용한 질감영상 분류)

  • Song, Kun-Woen;Kim, Gi-Seok;Do, Kyeong-Hoon;Ha, Yeong-Ho
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.1
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    • pp.116-127
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    • 1996
  • In this paper, a scheme of classification of scaled textured images using normalized pattern spectrum incorporating arbitrary scale changes based on mathematical morphology is proposed in more general environments considering camera's zoom-in and zoom-out function. The normalized pattern spectrum means that firstly pattern spectrum is calculated and secondly interpolation is performed to incorporate scale changes according to scale change ratio in the same textured image class. Pattern spectrum is efficiently obtained by using both opening and closing, that is, we calculate pattern spectrum by opening method for pixels which have value more than threshold and calculate pattern spectrum by closing method for pixels which have value less than threshold. Also we compare classification accuracy between gray scale method and binary method. The proposed approach has the advantage of efficient information extraction, high accuracy, less computation, and parallel implementation. An important advantage of the proposed method is that it is possible to obtain high classification accuracy with only (1:1) scale images for training phase.

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Color Modification Detection Using Normalization and Weighted Sum of Color Components (컬러 성분의 정규화와 가중치 합을 이용한 컬러 조작 검출)

  • Shin, Hyun Jun;Jeon, Jong Ju;Eom, Il Kyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.12
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    • pp.111-119
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    • 2016
  • Most commercial digital cameras acquire the colors of an image through the color filter array, and interpolate missing pixels of the image. Because of this fact, original pixels and interpolated pixels have different statistical characteristics. If colors of an image are modified, the color filter array pattern that consists of RGB channels is changed. Using this pattern change, a color forgery detection method were presented. The conventional method uses the number of pixels that exceeds the maximum or minimum value of pre-defined block by only exploiting green component. However, this algorithm cannot remove the flat area which is occurred when color is changed. And the conventional method has demerit that cannot detect the forged image with rare green pixels. In this paper, we propose an enhanced color forgery detection algorithm using the normalization and weighted sum of the color components. Our method can reduce the detection error by using all color components and removing flat area. Through simulations, we observe that our proposed method shows better detection performance compared to the conventional method.

A Texture Classification Based on LBP by Using Intensity Differences between Pixels (화소간의 명암차를 이용한 LBP 기반 질감분류)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.5
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    • pp.483-488
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    • 2015
  • This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

Digital Filter Algorithm based on Local Steering Kernel and Block Matching in AWGN Environment (AWGN 환경에서 로컬 스티어링 커널과 블록매칭에 기반한 디지털 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.910-916
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    • 2021
  • In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.

Detection of Defects on Repeated Multi-Patterned Images (반복되는 다수 패턴 영상에서의 불량 검출)

  • Lee, Jang-Hee;Yoo, Suk-In
    • Journal of KIISE:Software and Applications
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    • v.37 no.5
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    • pp.386-393
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    • 2010
  • A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

Recording of larger object by using two confocal lenses in digital holography (디지털 홀로그래피에서의 공초점 렌즈계를 이용한 보다 큰 물체의 기록)

  • 김성규;최현희;손정영
    • Korean Journal of Optics and Photonics
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    • v.14 no.3
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    • pp.244-248
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    • 2003
  • When confocal lenses are applied to a digital holography system, the interference pattern of a larger object size can be recorded on CCD. The angle of incoming light to the CCD can be reduced by the ratio of the two focal lengths of confocal lenses. The recordable spatial frequency is limited by the unit cell size of the CCD. Therefore the spatial frequency of interference on the CCD is lowered by reduction of the incoming light angle. By using confocal lenses , another merit can be achieved that the area of the zero order diffraction is reduced by the square of the ratio of two focal lengths at the numerical reconstruction.

Automated Green House Extraction Method Using Texture Information in High Spatial Resolution Satellite Images (텍스춰 기반의 자동 물체인식방법 연구: 비닐하우스를 중심으로)

  • Lee, Jong-Yeol;Kim, Byoung-Sun
    • Proceedings of the KSRS Conference
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    • 2008.03a
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    • pp.48-52
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    • 2008
  • 지형지물은 각각의 특징적 요인을 내포하고 있다. 이 특징적 요인들은, 공간해상도에 따라 정도의 차이가 있겠지만, 수집된 위성영상에도 반영된다. 이러한 요인들 중에서는 영상분류에 활용될 경우 영상 분류의 정확도를 높혀 주고, 때로는 이것이 거의 물체인식의 수준까지 기여할 수 있는 것들이 있다. 이 연구에서는 텍스춰 및 지형지물의 배열에 있어서 특징적 현상을 보이는 비닐하우스를 대상으로 spatial auto-corelation 개념을 기반으로 자동적으로 이를 인지하는 방법을 개발하였다. 사용된 알고리즘은 디지타이징과 같은 사람의 직접적인 개입이 없이 자동화된 방법으로 비닐하우스의 특정한 패턴이 반복적으로 나타나는 것을 감지할 수 있도록 개발되었다. 패턴의 인식에 더하여 비닐하우스의 기하학적 모양을 고려하는 방법도 도입하였다. 그럼으로써 비닐하우스의 추출에 단순히 화소 단위의 분석이 아닌 보다 객체지향적인 방법으로 비닐하우스를 추출하도록 하였다. 개발된 방법을 제주지역의 IKONOS에 적용시켜 본 결과, 연구대상지역 내의 비닐하우스가 매우 정확하게 적출되었다.

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A Method for Optimizing Threshold Value using Sit-plane Pattern (비트평면 패턴을 이용한 최적 임계화 방법)

  • 김하식;조남형;김윤호;이주신
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.583-586
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    • 2001
  • 본 연구는 영상에서 이진영상을 얻기위하여 최적의 임계값 결정을 영상에 나타난 물체의 형상정보를 근거로한 비트평면 패턴을 이용한 최적 임계화 방법을 제안한다. 제안된 방법은 원영상의 윤곽정보를 가장 많이 포함하는 최상위 비트평면을 사용하여 영상을 중복되지 않는 두 영역으로 구분한 뒤, 두영역의 화소 밝기값의 평균값을 각 각 구하고 두 평균값 사이에서 임계값을 설정하는 전역 임계화 알고리즘이다. 제안된 방법의 타당성을 검토하기 위하여 표준영상을 가지고 N 개의 비트평면으로 분할 한 후, 비트평면에서 전체영상을 중복되지 않는 물체의 영역과 배경영역으로 나누어 영상의 밝기를 비교한후, 두 영역의 영상 밝기의 중간 값을 추하여 임계값으로 결정한 결과 전체영상의 밝기값 분포만을 분석한 결과 보다 원영상의 윤곽을 더 충실히 얻을 수 있었다.

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Fast Variable-size Block Matching Algorithm for Motion Estimation Based on Bit-pattern (비트패턴을 기반으로 한 고속의 적응적 가변 블록 움직임 예측 알고리즘)

  • 신동식;안재형
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.372-379
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    • 2000
  • In this paper, we propose a fast variable-size block matching algorithm for motion estimation based on bit-pattern. Motion estimation in the proposed algorithm is performed after the representation of image sequence is transformed 8bit pixel values into 1bit ones depending on the mean value of search block, which brings a short searching time by reducing the computational complexity. Moreover, adaptive searching methods according to the motion information of the block make the procedure of motion estimation efficient by eliminating an unnecessary searching of low motion block and deepening a searching procedure in high motion block. Experimental results show that the proposed algorithm provides better performance-0.5dB PSNR improvement-than full search block matching algorithm with a fixed block size.

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A New Watermarking Method for Video (동영상을 위한 새로운 워터마킹 방법)

  • Kim, Dug-Ryung;Park, Sung-Han
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.97-106
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    • 1999
  • We propose a new watermarking method to embed a label in a video which is robust against the change of the group of picture. The proposed method embeds labels in the pixel domain, but detects the label in the DCT frequency domain. For embedding a label, the size of watermark based on the human visual system is calculated to keep a quality of videos. A lookup table haying the pixel patterns and the sequences of a sign of DCT coefficients is used for detecting a label in the DCT frequency domain. In this paper, we analyze bit error rates for labels of videos compressed by MPEG2 using the central limit theorem and compare the simulation results with previous methods.

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