• Title/Summary/Keyword: 영상 전처리

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Frame Skipping Algorithm for Minimization of Video Quality Variation (영상 품질 변화를 최소화하는 프레임 생략 알고리즘)

  • Park, Sang-Hyun;Lee, Sung-Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.8
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    • pp.1582-1588
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    • 2007
  • According to recently presented QoS architecture by 3GPP, a traffic conditioner may be deployed to provide conformance of the negotiated QoS. In this paper, a real-time frame-layer rate control method which can be applied to the traffic conditioner of 3GPP is proposed. The proposed rate control method uses an efficient frame skipping algorithm method for low computational complexity, and performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. The proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder.

Precision correction of satellite-based linear pushbroom-type CCD camera images (선형 CCD카메라 영상의 정밀 기하학적 보정)

  • 신동석;이영란;이흥규
    • Korean Journal of Remote Sensing
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    • v.14 no.2
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    • pp.137-148
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    • 1998
  • An algorithm developed for the precision correction of high resolution satellite images is introduced in this paper. In general, the polynomial warping algorithm which derives polynomial equations between GCPs extracted from an image and a base map requires many GCPs well-distributed over the image. The precision correction algorithm described in this paper is based on a sensor-orbit-Earth geometry, and therefore, it is capable of correcting a raw image using only 2-3 GCPs. This algorithm estimates the errors on the orbit determination and the attitude of the satellite by using a Kalman filter. This algorithm was implemented, tested and integrated into the KITSAT-3 image preprocessing software.

Development of Radiosynthetic Methods of 18F-THK5351 for tau PET Imaging (타우 PET영상을 위한 18F-THK5351의 표지방법 개발)

  • Park, Jun-Young;Son, Jeong-Min;Chun, Joong-Hyun
    • The Korean Journal of Nuclear Medicine Technology
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    • v.22 no.1
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    • pp.51-54
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    • 2018
  • Purpose $^{18}F-THK5351$ is the newly developed PET probe for tau imaging in alzheimer's disease. The purpose of study was to establish the automated production of $^{18}F-THK5351$ on a commercial module. Materials and Methods Two different approaches were evaluated for the synthesis of $^{18}F-THK5351$. The first approach (method I) included the nucleophilic $^{18}F$-fluorination of the tosylate precursor, subsequently followed by pre-HPLC purification of crude reaction mixture with SPE cartridge. In the second approach (method II), the crude reaction mixture was directly introduced to a semi-preparative HPLC without SPE purification. The radiosynthesis of $^{18}F-THK5351$ was performed on a commercial GE $TRACERlab^{TM}$ $FX-_{FN}$ module. Quality control of $^{18}F-THK5351$ was carried out to meet the criteria guidelined in USP for PET radiopharmaceuticals. Results The overall radiochemical yield of method I was $23.8{\pm}1.9%$ (n=4) as the decay-corrected yield (end of synthesis, EOS) and the total synthesis time was $75{\pm}3min$. The radiochemical yield of method II was $31.9{\pm}6.7%$ (decay-corrected, n=10) and the total preparation time was $70{\pm}2min$. The radiochemical purity was>98%. Conclusion This study shows that method II provides higher radiochemical yield and shorter production time compared to the pre-SPE purification described in method I. The $^{18}F-THK5351$ synthesis by method II will be ideal for routine clinical application, considering short physical half-life of fluorine-18 ($t_{1/2}=110min$).

Integrated Automatic Pre-Processing for Change Detection Based on SURF Algorithm and Mask Filter (변화탐지를 위한 SURF 알고리즘과 마스크필터 기반 통합 자동 전처리)

  • Kim, Taeheon;Lee, Won Hee;Yeom, Junho;Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.3
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    • pp.209-219
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    • 2019
  • Satellite imagery occurs geometric and radiometric errors due to external environmental factors at the acquired time, which in turn causes false-alarm in change detection. These errors should be eliminated by geometric and radiometric corrections. In this study, we propose a methodology that automatically and simultaneously performs geometric and radiometric corrections by using the SURF (Speeded-Up Robust Feature) algorithm and the mask filter. The MPs (Matching Points), which show invariant properties between multi-temporal imagery, extracted through the SURF algorithm are used for automatic geometric correction. Using the properties of the extracted MPs, PIFs (Pseudo Invariant Features) used for relative radiometric correction are selected. Subsequently, secondary PIFs are extracted by generated mask filters around the selected PIFs. After performing automatic using the extracted MPs, we could confirm that geometric and radiometric errors are eliminated as the result of performing the relative radiometric correction using PIFs in geo-rectified images.

Sign Language recognition Using Sequential Ram-based Cumulative Neural Networks (순차 램 기반 누적 신경망을 이용한 수화 인식)

  • Lee, Dong-Hyung;Kang, Man-Mo;Kim, Young-Kee;Lee, Soo-Dong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.5
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    • pp.205-211
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    • 2009
  • The Weightless Neural Network(WNN) has the advantage of the processing speed, less computability than weighted neural network which readjusts the weight. Especially, The behavior information such as sequential gesture has many serial correlation. So, It is required the high computability and processing time to recognize. To solve these problem, Many algorithms used that added preprocessing and hardware interface device to reduce the computability and speed. In this paper, we proposed the Ram based Sequential Cumulative Neural Network(SCNN) model which is sign language recognition system without preprocessing and hardware interface. We experimented with using compound words in continuous korean sign language which was input binary image with edge detection from camera. The recognition system of sign language without preprocessing got 93% recognition rate.

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Preprocessing Effect by Using k-means Clustering and Merging .Algorithms in MR Cardiac Left Ventricle Segmentation (자기공명 심장 영상의 좌심실 경계추출에서의 k 평균 군집화와 병합 알고리즘의 사용으로 인한 전처리 효과)

  • Ik-Hwan Cho;Jung-Su Oh;Kyong-Sik Om;In-Chan Song;Kee-Hyun Chang;Dong-Seok Jeong
    • Journal of Biomedical Engineering Research
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    • v.24 no.2
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    • pp.55-60
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    • 2003
  • For quantitative analysis of the cardiac diseases. it is necessary to segment the left-ventricle (LY) in MR (Magnetic Resonance) cardiac images. Snake or active contour model has been used to segment LV boundary. However, the contour of the LV front these models may not converge to the desirable one because the contour may fall into local minimum value due to image artifact inside of the LY Therefore, in this paper, we Propose the Preprocessing method using k-means clustering and merging algorithms that can improve the performance of the active contour model. We verified that our proposed algorithm overcomes local minimum convergence problem by experiment results.

Geometrical Feature-Based Detection of Pure Facial Regions (기하학적 특징에 기반한 순수 얼굴영역 검출기법)

  • 이대호;박영태
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.773-779
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    • 2003
  • Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

Real-time Volume Rendering using Point-Primitive (포인트 프리미티브를 이용한 실시간 볼륨 렌더링 기법)

  • Kang, Dong-Soo;Shin, Byeong-Seok
    • Journal of Korea Multimedia Society
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    • v.14 no.10
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    • pp.1229-1237
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    • 2011
  • The volume ray-casting method is one of the direct volume rendering methods that produces high-quality images as well as manipulates semi-transparent object. Although the volume ray-casting method produces high-quality image by sampling in the region of interest, its rendering speed is slow since the color acquisition process is complicated for repetitive memory reference and accumulation of sample values. Recently, the GPU-based acceleration techniques are introduced. However, they require pre-processing or additional memory. In this paper, we propose efficient point-primitive based method to overcome complicated computation of GPU ray-casting. It presents semi-transparent objects, however it does not require preprocessing and additional memory. Our method is fast since it generates point-primitives from volume dataset during sampling process and it projects the primitives onto the image plane. Also, our method can easily cope with OTF change because we can add or delete point-primitive in real-time.

Face Detection Algorithm Using Pulse-Coupled Neural Network in Color Images (컬러영상에서 Pulse-Coupled Neural Network를 이용한 얼굴 추출 알고리즘)

  • Lim, Young-Wan;Na, Jin-Hee;Choi, Jin-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.5
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    • pp.617-622
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    • 2004
  • In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of the skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value (255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking coefficient of Pulse-Coupled Neural Network.

Detection of Traffic Light using Color after Morphological Preprocessing (형태학적 전처리 후 색상을 이용한 교통 신호의 검출)

  • Kim, Chang-dae;Choi, Seo-hyuk;Kang, Ji-hun;Ryu, Sung-pil;Kim, Dong-woo;Ahn, Jae-hyeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.367-370
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    • 2015
  • This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

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