• Title/Summary/Keyword: Region Normalization

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Region-Segmental Scheme in Local Normalization Process of Digital Image (디지털영상 국부정규화처리의 영역분할 구도)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.78-85
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    • 2007
  • This paper presents a segmental scheme for regions-composed images in local normalization process. The scheme is based on local statistics computed through a moving window. The normalization algorithm uses linear or nonlinear functions to transfer the pixel distribution and the homogeneous affine of regions which is corrupted by additive noise. It adjusts the mean and standard deviation for nearest-neighbor interpoint distance between current and the normalized image signals and changes the segmentation performance according to local statistics and parameter variation adaptively. The performance of newly advanced local normalization algorithm is evaluated and compared to the performance of conventional normalization methods. Experimental results are presented to show the region segmentation properties of these approaches.

Speed Control of PMSM with Current Controller in Overmodulation Region (과변조 영역에서의 전류제어를 가지는 영구자석형 동기 전동기의 속도제어)

  • Park, Jin-Sik;Kim, Hag-Wone;Youn, Myung-Joong
    • Proceedings of the KIPE Conference
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    • 2005.07a
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    • pp.251-253
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    • 2005
  • This paper presents a study on a current control of a PM synchronous motor which is fed by two-level voltage source inverter in the high modulation index area. In order to increase dynamic response and extend speed limit caused by voltage limit, overmodulation method is generally used. The current control in overmodulation have voltage limit. So larger voltage command than voltage limit should be diminished. In this paper, the problem conventional normalization method is analyzed and New normalization method in overmodulation region is proposed.

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The Distribution Characteristics of Salt Contaminants in West Coast Region with the Distance from Sea (해안도달 거리에 따른 서해안 지역 염해 오손물의 분포특성)

  • Choi, Nam-Ho;Han, Sang-Ok
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.50 no.6
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    • pp.276-280
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    • 2001
  • This paper presents the result of a study on the distribution characteristics of salt contaminants in the west coast region, from Inchon to Yearsoo, of South Korea. To evaluate the distribution characteristics of salt contaminants, we had measured the equivalent salt deposit density(ESDD) with brush wiping method for thirteen month(from May 1999 to June 2000). Under the consideration on the measuring interval and method, normalization method was applied for the ESDD data. Besides the measurement, the chemical analysis (chromatography) was carried to investigate the relationship, between the electrical property and the amount of specific ingredient, such as sodium, magnesium and chloride. From the result, we could get the representative value of contamination for each site and distribution characteristics of salt contaminants with the distance from sea in the west coast.

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Gaze Tracking Using a Modified Starburst Algorithm and Homography Normalization (수정 Starburst 알고리즘과 Homography Normalization을 이용한 시선추적)

  • Cho, Tai-Hoon;Kang, Hyun-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.5
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    • pp.1162-1170
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    • 2014
  • In this paper, an accurate remote gaze tracking method with two cameras is presented using a modified Starburst algorithm and honography normalization. Starburst algorithm, which was originally developed for head-mounted systems, often fails in detecting accurate pupil centers in remote tracking systems with a larger field of view due to lots of noises. A region of interest area for pupil is found using template matching, and then only within this area Starburst algorithm is applied to yield pupil boundary candidate points. These are used in improved RANSAC ellipse fitting to produce the pupil center. For gaze estimation robust to head movement, an improved homography normalization using four LEDs and calibration based on high order polynomials is proposed. Finally, it is shown that accuracy and robustness of the system is improved using two cameras rather than one camera.

Face inpainting via Learnable Structure Knowledge of Fusion Network

  • Yang, You;Liu, Sixun;Xing, Bin;Li, Kesen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.877-893
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    • 2022
  • With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

Empirical Analysis of DEA models Validity for R&D Project Performance Evaluation : Focusing on Rank Correlation with Normalization Index (R&D 프로젝트 성과평가를 위한 DEA모형의 타당성 실증분석 : 정규화지표와의 순위상관을 중심으로)

  • Park, Sung-Min
    • IE interfaces
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    • v.24 no.4
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    • pp.314-322
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    • 2011
  • This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

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.

A Method for Improving Vein Recognition Performance by Illumination Normalization (조명 정규화를 통한 정맥인식 성능 향상 기법)

  • Lee, Eui Chul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.2
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    • pp.423-430
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    • 2013
  • Recently, the personal identification technologies using vein pattern of back of the hand, palm, and finger have been developed actively because it has the advantage that the vein blood vessel in the body is impossible to damage, make a replication and forge. However, it is difficult to extract clearly the vein region from captured vein images through common image prcessing based region segmentation method, because of the light scattering and non-uniform internal tissue by skin layer and inside layer skeleton, etc. Especially, it takes a long time for processing time and makes a discontinuity of blood vessel just in a image because it has non-uniform illumination due to use a locally different adaptive threshold for the binarization of acquired finger-vein image. To solve this problem, we propose illumination normalization based fast method for extracting the finger-vein region. The proposed method has advantages compared to the previous methods as follows. Firstly, for remove a non-uniform illumination of the captured vein image, we obtain a illumination component of the captured vein image by using a low-pass filter. Secondly, by extracting the finger-vein path using one time binarization of a single threshold selection, we were able to reduce the processing time. Through experimental results, we confirmed that the accuracy of extracting the finger-vein region was increased and the processing time was shortened than prior methods.

The Attenuation Structure of the South Korea: A review

  • Chung, T. W.;Noh, M. H.;Matsumoto, S.
    • Journal of the Korean Geophysical Society
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    • v.9 no.3
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    • pp.199-207
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    • 2006
  • Fukuoka earthquake on March 20, 2005 showed the potential hazard of large events out of S. Korea. From the viewpoint of seismic hazard, seismic amplitude decrease Q-1 is very important. Related to the crustal cracks induced by the earthquakes, the value of Q-1- high Q-1 regions are more attenuating than low Q-1 regions - shows a correlation with seismic activity; relatively higher values of Q-1 have been observed in seismically active areas than in stable areas. For the southeastern and central S. Korea, we first simultaneously estimated QP-1 and QS-1 by applying the extended coda-normalization method to KIGAM and KNUE network data. Estimated QP-1 and QS-1 values are 0.009 f-1.05 and 0.004 f-0.70 for southeastern S. Korea and 0.003 f -0.54 and 0.003 f -0.42 for central S. Korea, respectively. These values agree with those of seismically inactive regions such as shield. The low QLg-1 value, 0.0018f -0.54 was also obtained by the coda normalization method. In addition, we studied QLg-1 by applying the source pair/receiver pair (SPRP) method to both domestic and far-regional events. The obtained QLg-1 for all Fc is less than 0.002, which is reasonable value for a seismically inactive region.

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