• Title/Summary/Keyword: Adaptive Threshold Range

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Fractal Image Compression Using Adaptive Selection of Block Approximation Formula (블록 근사화식의 적응적 선택을 이용한 프랙탈 영상 부호화)

  • Park, Yong-Ki;Park, Chul-Woo;Kim, Doo-Young
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.12
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    • pp.3185-3199
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    • 1997
  • This paper suggests techniques to reduce coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, we choose new approximation coefficients using a non-linear approximation of luminance term. This boosts the fidelity. Our experiment employing the above methods shows enhancement in the coding time more than two times over traditional coding methods and shows improvement in PSNR value by about 1-3dB at the same com- pression rate.

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A Low Power, Wide Tuning Range VCO with Two-Step Negative-Gm Calibration Loop (2단계 자동 트랜스컨덕턴스 조절 기능을 가진 저전력, 광대역 전압제어 발진기의 설계)

  • Kim, Sang-Woo;Park, Joon-Sung;Pu, Young-Gun;Hur, Jeong;Lee, Kang-Yoon
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.47 no.2
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    • pp.87-93
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    • 2010
  • This paper presents a low-power, wide tuning range VCO with automatic two-step negative-Gm calibration loop to compensate for the process, voltage and temperature variation. To cover the wide tuning range, digital automatic negative-Gm tuning loop and analog automatic amplitude calibration loop are used. Adaptive body biasing (ABB) technique is also adopted to minimize the power consumption by lowering the threshold voltage of transistors in the negative-Gm core. The power consumption is 2 mA to 6mA from a 1.2 V supply. The VCO tuning range is 2.65 GHz, from 2.35 GHz to 5 GHz. And the phase noise is -117 dBc/Hz at the 1 MHz offset when the center frequency is 3.2 GHz.

Classification of the PVC Using The Fuzzy-ART Network Based on Wavelet Coefficient (웨이브렛 계수에 근거한 Fuzzy-ART 네트워크를 이용한 PVC 분류)

  • Park, K. L;Lee, K. J.;lee, Y. S.;Yoon, H. R.
    • Journal of Biomedical Engineering Research
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    • v.20 no.4
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    • pp.435-442
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    • 1999
  • A fuzzy-ART(adaptive resonance theory) network for the PVC(premature ventricular contraction) classification using wavelet coefficient is designed. This network consists of the feature extraction and learning of the fuzzy-ART network. In the first step, we have detected the QRS from the ECG signal in order to set the threshold range for feature extraction and the detected QRS was divided into several frequency bands by wavelet transformation using Haar wavelet. Among the low-frequency bands, only the 6th coefficient(D6) are selected as the input feature. After that, the fuzzy-ART network for classification of the PVC is learned by using input feature which comprises of binary data converted by applying threshold to D6. The MIT/BIH database including the PVC is used for the evaluation. The designed fuzzy-ART network showed the PVC classification ratio of 96.52%.

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Automatic Liver Segmentation of a Contrast Enhanced CT Image Using a Partial Histogram Threshold Algorithm (부분 히스토그램 문턱치 알고리즘을 사용한 조영증강 CT영상의 자동 간 분할)

  • Kyung-Sik Seo;Seung-Jin Park;Jong An Park
    • Journal of Biomedical Engineering Research
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    • v.25 no.3
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    • pp.189-194
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    • 2004
  • Pixel values of contrast enhanced computed tomography (CE-CT) images are randomly changed. Also, the middle liver part has a problem to segregate the liver structure because of similar gray-level values of a pancreas in the abdomen. In this paper, an automatic liver segmentation method using a partial histogram threshold (PHT) algorithm is proposed for overcoming randomness of CE-CT images and removing the pancreas. After histogram transformation, adaptive multi-modal threshold is used to find the range of gray-level values of the liver structure. Also, the PHT algorithm is performed for removing the pancreas. Then, morphological filtering is processed for removing of unnecessary objects and smoothing of the boundary. Four CE-CT slices of eight patients were selected to evaluate the proposed method. As the average of normalized average area of the automatic segmented method II (ASM II) using the PHT and manual segmented method (MSM) are 0.1671 and 0.1711, these two method shows very small differences. Also, the average area error rate between the ASM II and MSM is 6.8339 %. From the results of experiments, the proposed method has similar performance as the MSM by medical Doctor.

Dense Optical flow based Moving Object Detection at Dynamic Scenes (동적 배경에서의 고밀도 광류 기반 이동 객체 검출)

  • Lim, Hyojin;Choi, Yeongyu;Nguyen Khac, Cuong;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.5
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    • pp.277-285
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    • 2016
  • Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

Improved Gate Drive Circuit for High Power IGBTs with a Novel Overvoltage Protection Scheme (과전압 제한 기능을 갖는 새로운 IGBT 게이트 구동회로)

  • Lee, Hwang-Geol;Lee, Yo-Han;Suh, Bum-Seok;Hyun, Dong-Seok;Lee, Jin-Woo
    • Proceedings of the KIEE Conference
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    • 1996.11a
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    • pp.346-349
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    • 1996
  • In application of high power IGBT PWM inverters, the treatable power range is considerably limited due to the overvoltage caused by the stray inductance components within the power circuit. This paper proposes a new gate drive circuit for IGBTs which can actively suppress the overvoltage across the driven IGBT at turn-off and the overvoltage across the opposite IGBT at turn-on while preserving the most simple and reliable power circuit. The turn-off driving scheme has adaptive feature to the amplitude of collector current, so that the overvoltage is limited much effectively at the larger collector current. The turn-on scheme is to decrease the rising rate of the collector current by increasing input capacitance during turn-on transient when the gate-emitter voltage is greater than threshold voltage. The experimental results under various normal and fault conditions prove the effectiveness of the proposed circuit.

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Color Image Coding using Variable Block of Fractal (프랙탈 기반의 가변블록을 이용한 컬러영상 부호화)

  • Park, Jae-Hong;Park, Cheol-Woo
    • Journal of the Korean Society of Radiology
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    • v.8 no.7
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    • pp.435-441
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    • 2014
  • This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the RGB image compression rate and image quality, such as gray-level images and showed good.

Fractal Image Coding for Improve the Quality of Medical Images (의료영상의 화질개선을 위한 프랙탈 영상 부호화)

  • Park, Jaehong;Park, Cheolwoo;Yang, Wonseok
    • Journal of the Korean Society of Radiology
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    • v.8 no.1
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    • pp.19-26
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    • 2014
  • This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, we choose new approximation coefficients using a non-linear approximation of luminance term. This boosts the fidelity. Our experiment employing the above methods shows enhancement in the coding time more than two times over traditional coding methods and shows improvement in PSNR value by about 1-3dB at the same compression rate.

The YIQ Model of Computed Tomography Color Image Variable Block with Fractal Image Coding (전산화단층촬영 칼라영상의 YIQ모델을 가변블록 이용한 프랙탈 영상 부호화)

  • Park, Jae-Hong;Park, Cheol-Woo
    • Journal of the Korean Society of Radiology
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    • v.10 no.4
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    • pp.263-270
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    • 2016
  • This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the YIQ image compression rate and image quality, such as RGB images and showed good.