• Title/Summary/Keyword: 스케일 특성

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Color Image Zero-Watermarking on DCT Domain through Comparison of Two Channels (두 채널 비교를 통한 DCT 영역 컬러 이미지 제로-워터마킹)

  • Kim, HyoungDo
    • The Journal of the Korea Contents Association
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    • v.15 no.9
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    • pp.11-20
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    • 2015
  • Digital watermarking provides electronic means for proving the copyrights of distributed digital media copies. Research on digital watermarking for images is recently directed toward that for color images extensively used in real life, based on the substantial results in digital watermarking for gray-scale images. Color images have multiple channels, each of which corresponds to a gray-scale image. While there are some watermarking techniques for color images that just apply those for gray-scale images to one channel of the color images, the correlation characteristics between the channels are not considered in them. This paper proposes a zero-watermarking technique that makes keys via combining an image dependent watermark, created through comparing two channels of the color image and copyright watermark scrambled. Due to zero-watermarking, it does not change anything of cover(host) images. Watermark images are robust against some common attacks such as sharpening, blurring, JPEG lossy compression, scaling, and cropping.

Multi-resolution Representation of 2D Point Data (2차원 점 데이터의 다중해상도 표현)

  • Yun, Seong-Min;Lee, Mun-Bae;Park, Sang-Hun
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.7
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    • pp.768-774
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    • 2010
  • Reconstruction of implicit surfaces from scattered point data sets have been developed in various engineering and scientific studies. In this paper, we represent a method to construct functions of 2D point data using multi-scale kernels and show it can be applied to graphics applications needed to access data in real-time. Our approach is similar to previous work in that a set of coefficients of the functions are calculated and stored in the preprocessing stage and function values at arbitrary positions are evaluated for real-time applications, however, it is different from others in that users can choose detail levels freely in real-time processing stage. The reason why the functions implicitly supports multi-resolution results from the mathematical properties of multi-scale kernels, and proposed method can be expanded to represent multi-resolution functions of n-dimensional data.

Modeling of Nano-scale FET(Field Effect Transistor : FinFET) (나노-스케일 전계 효과 트랜지스터 모델링 연구 : FinFET)

  • Kim, Ki-Dong;Kwon, Oh-Seob;Seo, Ji-Hyun;Won, Tae-Young
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.41 no.6
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    • pp.1-7
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    • 2004
  • We performed two-dimensional (20) computer-based modeling and simulation of FinFET by solving the coupled Poisson-Schrodinger equations quantum-mechanically in a self-consistent manner. The simulation results are carefully investigated for FinFET with gate length(Lg) varying from 10 to 80nm and with a Si-fin thickness($T_{fin}$) varying from 10 to 40nm. Current-voltage (I-V) characteristics are compared with the experimental data. Device optimization has been performed in order to suppress the short-channel effects (SCEs) including the sub-threshold swing, threshold voltage roll-off, drain induced barrier lowering (DIBL). The quantum-mechanical simulation is compared with the classical appmach in order to understand the influence of the electron confinement effect. Simulation results indicated that the FinFET is a promising structure to suppress the SCEs and the quantum-mechanical simulation is essential for applying nano-scale device structure.

Segmentation of MR Brain Image Using Scale Space Filtering and Fuzzy Clustering (스케일 스페이스 필터링과 퍼지 클러스터링을 이용한 뇌 자기공명영상의 분할)

  • 윤옥경;김동휘;박길흠
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.339-346
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    • 2000
  • Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.

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A Study on Model Establishment and Structural Analysis for Gun Blast Load (기총 폭발 하중에 대한 모델 수립과 구조 해석에 관한 연구)

  • Kim, Dae-Kwan;Han, Jae-Hung;Jang, Jae-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.7
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    • pp.33-39
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    • 2005
  • A mathematical model, GUNBLAST, of blast waves emitted from a gun muzzle is established, and structural response analyses for the blast load are performed. The blast wave can be divided into two kinds of waves, free field and reflected blast waves. In this research, the free field blast wave model is established by the use of a scaling approach, and the reflected blast wave is calculated by using the oblique shock theory and computational fluid dynamic calculation. GUNBLAST is applied to two kinds of structural models. To investigate the effect of the muzzle distance from a structural surface, the blast waves on a plate for various muzzle distances are compared to uniform loads. Moreover, the transient response analysis of an aircraft wing model with a 12.7mm gun is carried out by using MSC/NASTRAN. From the results, it can be shown that the blast wave can cause broad random vibration and high frequency damage to equipments mounted in the aircraft.

Image Interpolation Using Linear Modeling for the Absolute Values of Wavelet Coefficients Across Scale (스케일간 웨이블릿 계수 절대치의 선형 모델링을 이용한 영상 보간)

  • Kim Sang-Soo;Eom Il-Kyu;Kim Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.19-26
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    • 2005
  • Image interpolation in the wavelet domain usually takes advantage of the probabilistic models for the intrascale statistics and the interscale dependency. In this paper, we adopt the linear model for the absolute values of wavelet coefficients of interpolated image across scale to estimate the variances of extrapolated bands. The proposed algorithm uses randomly generated wavelet coefficients based on the estimated parameters for probabilistic model. Random number generation according to the estimated probabilistic model may induce the 'salt and pepper' noise in subbands. We reduce the noise power by Wiener filtering. We observe that the proposed method generates the histogram of the subband coefficients similar to the that of original image. Experimental results show that our method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

Optimal Network Selection Method for Artificial Neural Network Downscaling Method (인공신경망 Downscaling모형에 있어서 최적신경망구조 선택기법)

  • Kang, Boo-Sik;Ryu, Seung-Yeop;Moon, Su-Jin
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1605-1609
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    • 2010
  • CGCM3.1 SRES B1 시나리오의 2D 변수들을 입력값으로 인공신경망 모형을 이용한 스케일 상세화기법으로 강부식(2009)은 소양강댐 유역의 월 누적강수 경향분석을 실시하였다. 원시 GCM 시나리오를 스케일 상세화 시키기 위한 기법의 하나로 인공신경망 모형을 사용할 수 있는데, 이 경우 GCM에서 모의되는 강수플럭스, 해면기압, 지표면 근처에서의 일 평균온도, 지표면 근처에서의 일평균온도, 지표면으로부터 발생하는 잠열플럭스 등과 같은 22개의 변수를 잠재적인 예측인자로 사용하여 신경망을 구성하게 된다. 입력변수세트의 구성은 인공신경망의 계산 효율을 좌우하는 중요한 요소라 할 수 있다. 본 연구에서는 변수의 물리적 특성을 고려하여 순차적인 변수선택을 통한 신경망 입력변수 세트를 구성하고 입력세트 간의 학습성과 비교를 통하여, 최적 입력변수 선정 및 신경망의 학습효과를 높일 수 있는 방법에 대해 연구하였다. 물리적 상관성이 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 하여 순차적인 케이스를 학습해본 결과 huss와 ps를 입력변수로 하는 케이스에 대해서 적은 오차와 높은 상관성을 보였다, 또한, 신경망의 학습 효과를 높이기 위해 홍수기와 비홍수기로 구분하여 학습한 결과 홍수기와 비홍수기로 구분하여 신경망을 구성하였을 경우가 향상된 모의값을 나타내었다. 기후변화모의자료는 CCCma(Canadian Center for Climate Modeling and Analysis)에서 제공되는 CGCM3.1/T63 20C3M 시나리오를 사용하였으며, 관측값으로는 AWS에서 제공된 일 누적강수를 사용하였다. 인공신경망의 학습기간은 1997년부터 2000년이며, 검증기간은 2001년부터 2004년으로 구성하였다.

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Effects of the Modifiable Areal Unit Problem (MAUP) on a Spatial Interaction Model (공간 상호작용 모델에 대한 공간단위 수정가능성 문제(MAUP)의 영향)

  • Kim, Kam-Young
    • Journal of the Korean Geographical Society
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    • v.46 no.2
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    • pp.197-211
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    • 2011
  • Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

A Study on Interior Wall Color based on Measurement of Emotional Responses (감성 측정에 따른 실내 벽면 색채에 관한 연구)

  • Kim, Ju-Yeon;Lee, Hyun-Soo
    • Science of Emotion and Sensibility
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    • v.12 no.2
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    • pp.205-214
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    • 2009
  • This paper addresses analyzing affective color data for emotional interior design. Both the physical and psychological patterns for spatial colors were tested on thirty subjects, of which fifteen were male. All subjects participated in both the physiological and psychological experiments. The data on the reflecting subjects' affective moods is gathered through EEG physical experiments and SD (Semantic Differential Scale) method surveys. This research has suggested the relation of both experiments through affective color response. The methods of SPSS 10.0 and TeleScan Version 2 are used for analyzing response data to coordinate the colour palette with changeable moods. From the analysis of statistical data, all of the visual stimuli related emotional keywords and physiological responses. Finally, the initial goal of this research is to construct an affective colour database that is tested through human color perception by physical and psychological experiments.

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Image Similarity Retrieval using an Scale and Rotation Invariant Region Feature (크기 및 회전 불변 영역 특징을 이용한 이미지 유사성 검색)

  • Yu, Seung-Hoon;Kim, Hyun-Soo;Lee, Seok-Lyong;Lim, Myung-Kwan;Kim, Deok-Hwan
    • Journal of KIISE:Databases
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    • v.36 no.6
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    • pp.446-454
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    • 2009
  • Among various region detector and shape feature extraction method, MSER(Maximally Stable Extremal Region) and SIFT and its variant methods are popularly used in computer vision application. However, since SIFT is sensitive to the illumination change and MSER is sensitive to the scale change, it is not easy to apply the image similarity retrieval. In this paper, we present a Scale and Rotation Invariant Region Feature(SRIRF) descriptor using scale pyramid, MSER and affine normalization. The proposed SRIRF method is robust to scale, rotation, illumination change of image since it uses the affine normalization and the scale pyramid. We have tested the SRIRF method on various images. Experimental results demonstrate that the retrieval performance of the SRIRF method is about 20%, 38%, 11%, 24% better than those of traditional SIFT, PCA-SIFT, CE-SIFT and SURF, respectively.