• Title/Summary/Keyword: image pre-processing

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Establishment Status of the Korea Ocean Satellite Center and GOCI-Data Distribution System (해양위성센터 구축 현황 및 GOCI 자료배포시스템 소개)

  • Yang, Chan-Su;Bae, Sang-Soo;Han, Hee-Jeong;Cho, Seong-Ick;Ahn, Yu-Hwan
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.367-370
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    • 2009
  • 한국해양연구원에서는 2009년 발사 예정인 통신해양기상위성(COMS: Communication, Ocean and Meteorological Satellite)의 해색센서인 정지궤도 해양위성(GOCI: Geostationary Ocean Color Imager) 데이터의 수신, 처리, 배포를 위한 해양위성센터(KOSC: Korea Ocean Satellite Center)를 구축하고 있다. 2005년 "해양위성센터 구축사업"의 시작으로, 전파 수신 환경 등의 조건을 고려하여, 안산에 위치한 한국해양연구원 본원으로 해양위성센터의 위치를 최종 확정하여 구축을 진행하고 있다. 2009년 3월 현재 수신시스템(GDAS: GOCI Data Aquisition System), 자료전처리시스템(IMPS: Image Pre-processing System), 자료처리시스템(GDPS: GOCI Data Processing System), 자료관리 시스템(DMS: Data Management System), 통합감시제어시스템(TMC: Total Management & Controlling System), 기관간 자료교환시스템(EDES: External Data Exchange System) 등이 구축 완료되었고, 위성자료 배포시스템(DDS: Data Distribution System)을 구축하고 있다. 고용량 데이터의 원활한 전송을 위한 데이터센터를 비롯하여 사용자관점에서의 시스템 구축을 추진하고 있으며, 위성 발사 후 사용자 등록을 시작할 계획이다.

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A Study on Traffic Light Detection (TLD) as an Advanced Driver Assistance System (ADAS) for Elderly Drivers

  • Roslan, Zhafri Hariz;Cho, Myeon-gyun
    • International Journal of Contents
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    • v.14 no.2
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    • pp.24-29
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    • 2018
  • In this paper, we propose an efficient traffic light detection (TLD) method as an advanced driver assistance system (ADAS) for elderly drivers. Since an increase in traffic accidents is associated with the aging population and an increase in elderly drivers causes a serious social problem, the provision of ADAS for older drivers via TLD is becoming a necessary(Ed: verify word choice: necessary?) public service. Therefore, we propose an economical TLD method that can be implemented with a simple black box (built in camera) and a smartphone in the near future. The system utilizes a color pre-processing method to differentiate between the stop and go signals. A mathematical morphology algorithm is used to further enhance the traffic light detection and a circular Hough transform is utilized to detect the traffic light correctly. From the simulation results of the computer vision and image processing based on a proposed algorithm on Matlab, we found that the proposed TLD method can detect the stop and go signals from the traffic lights not only in daytime, but also at night. In the future, it will be possible to reduce the traffic accident rate by recognizing the traffic signal and informing the elderly of how to drive by voice.

Real-time Human Detection under Omni-dir ectional Camera based on CNN with Unified Detection and AGMM for Visual Surveillance

  • Nguyen, Thanh Binh;Nguyen, Van Tuan;Chung, Sun-Tae;Cho, Seongwon
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1345-1360
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    • 2016
  • In this paper, we propose a new real-time human detection under omni-directional cameras for visual surveillance purpose, based on CNN with unified detection and AGMM. Compared to CNN-based state-of-the-art object detection methods. YOLO model-based object detection method boasts of very fast object detection, but with less accuracy. The proposed method adapts the unified detecting CNN of YOLO model so as to be intensified by the additional foreground contextual information obtained from pre-stage AGMM. Increased computational time incurred by additional AGMM processing is compensated by speed-up gain obtained from utilizing 2-D input data consisting of grey-level image data and foreground context information instead of 3-D color input data. Through various experiments, it is shown that the proposed method performs better with respect to accuracy and more robust to environment changes than YOLO model-based human detection method, but with the similar processing speeds to that of YOLO model-based one. Thus, it can be successfully employed for embedded surveillance application.

Frontal Asymmetry Analysis of Theta Wave in the Audio Emotional Experiment Revealed by Event-related Spectral Perturbation

  • Du, Ruoyu;Lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.992-994
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    • 2014
  • Hemispheric asymmetry in prefrontal activation have been proposed in two decades ago, as measured by electroencephalographic (EEG) power in the theta band (4-8Hz), is related to reactivity to affectively pleasure audio stimuli. In this study, we designed an emotional audio stimulus experiment in order to verify frontal EEG asymmetry by analyzing ERSP results. Thirty healthy college students volunteered the stimulus experiment with the standard IADS affective sounds. These affective sound clips are classified in three emotion states, happy, neutral and fear. ERSP image results revealed that there are the stronger responses of high arousal (fear and happy) in the left prefrontal lobe, while the stronger responses of low arousal (neutral) in the right pre-frontal lobe. However, the high pleasure emotions (happy) can elicit greater relative right EEG activity, while the low and middle pleasure emotions (fear and neutral) can elicit the greater relative left EEG activity. Additionally, the most response differences of theta band have been found out in the medial frontal lobe, which is proved as the frontal midline theta.

Design of an efficient learning-based face detection system (학습기반 효율적인 얼굴 검출 시스템 설계)

  • Kim Hyunsik;Kim Wantae;Park Byungjoon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.3
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    • pp.213-220
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    • 2023
  • Face recognition is a very important process in video monitoring and is a type of biometric technology. It is mainly used for identification and security purposes, such as ID cards, licenses, and passports. The recognition process has many variables and is complex, so development has been slow. In this paper, we proposed a face recognition method using CNN, which has been re-examined due to the recent development of computers and algorithms, and compared with the feature comparison method, which is an existing face recognition algorithm, to verify performance. The proposed face search method is divided into a face region extraction step and a learning step. For learning, face images were standardized to 50×50 pixels, and learning was conducted while minimizing unnecessary nodes. In this paper, convolution and polling-based techniques, which are one of the deep learning technologies, were used for learning, and 1,000 face images were randomly selected from among 7,000 images of Caltech, and as a result of inspection, the final recognition rate was 98%.

The Effect of the Milk Yield and Performance Analysis of Robot Milking System (로봇 착유시스템의 착유성능 및 착유량에 미치는 영향)

  • Kim, W.;Lee, D.W.
    • Journal of Animal Environmental Science
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    • v.15 no.1
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    • pp.29-36
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    • 2009
  • The authors of this study have developed a robot milking system composed of a multi-articular manipulator, a teat-cup attachment system, and an image processing system. In order to verify the efficacy of this system, we have conducted a performance analysis and measurement experiment of milk yield, using dairy cattle. It was concluded that teat recognition using the image processing system, teat-cup attachment, and detachment system did not binder milking. The milking yield of the robot milking system was analyzed based on a lactation curve. As a result, it was determined that the use of a robot milking system had no significant effects on milking yields. The robot milking system described in this study is designed specifically with a focus on teat-cup attachment and detachment performance, as well as the effect of these factors on milking yield. In the future, in-depth studies regarding the washing of the teats prior to milking, teat massage, pre-treatment and post-treatment processes after milking, and disinfection processes shall be conducted, in order to render this system feasible for use in an actual milking parlor.

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JND based Illumination and Color Restoration Using Edge-preserving Filter (JND와 경계 보호 평탄화 필터를 이용한 휘도 및 색상 복원)

  • Han, Hee-Chul;Sohn, Kwan-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.6
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    • pp.132-145
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    • 2009
  • We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

Radiologic assessment of bone healing after orthognathic surgery using fractal analysis

  • Park Kwan-Soo;Heo Min-Suk;Lee Sam-Sun;Choi Soon-Chul;Park Tae-Won;Jeon In-Seong;Kim Jong-Dae
    • Imaging Science in Dentistry
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    • v.32 no.4
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    • pp.201-206
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    • 2002
  • Purpose : To evaluate the radiographic change of operation sites after orthognathic surgery using the digital image processing and fractal analysis. Materials and Methods : A series of panoramic radiographs of thirty-five randomly selected patients who had undergone mandibular orthognathic surgery (bilateral sagittal split ramus osteotomy) without clinical complication for osseous healing, were taken. The panoramic radiographs of each selected patient were taken at pre-operation (stage 0), 1 or 2 days after operation (stage 1), 1 month after operation (stage 2), 6 months after operation (stage 3), and 12 months after operation (stage 4). The radiographs were digitized at 600 dpi, 8 bit, and 256 gray levels. The region of interest, centered on the bony gap area of the operation site, was selected and the fractal dimension was calculated by using the tile-counting method. The mean values and standard deviations of fractal dimension for each stage were calculated and the differences among stage 0, 1, 2, 3, and 4 were evaluated through repeated measures of the ANOVA and paired t-test. Results : The mean values and standard deviations of the fractal dimensions obtained from stage 0, 1, 2, 3, and 4 were 1.658±0.048, 1.580±0.050, 1.607±0.046, 1.624±0.049, and 1.641 ±0.061, respectively. The fractal dimensions from stage 1 to stage 4 were shown to have a tendency to increase (p < 0.05). Conclusion: The tendency of the fractal dimesion to increase relative to healing time may be a useful means of evaluating post-operative bony healing of the osteotomy site.

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Introduction to Image Pro-processing Subsystem of Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI) 전처리시스템)

  • Seo, Seok-Bae;Lim, Hyun-Su;Ahn, Sang-Il
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.167-173
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    • 2010
  • This paper introduces Geostationary Ocean Color Imager, IMage Pre-processing Subsystem (GOCI IMPS) of Communication, Ocean, and Meteorological Satellite (COMS), and describes its functions, development states, and operational concepts. The primary and backup systems of GOCI IMPS have been installed in Korea Ocean Satellite Center (KOSC) and Satellite Operation Center (SOC) and the system are the prelaunch test phase after completing all required tests. It is expected that the GOCI data observed continuously over the Korea Peninsular in the geostationary orbit will be usefully utilized in marine environment research fields such as sea surface temperature changes or marine ecosystems.

Shadow Removal based on the Deep Neural Network Using Self Attention Distillation (자기 주의 증류를 이용한 심층 신경망 기반의 그림자 제거)

  • Kim, Jinhee;Kim, Wonjun
    • Journal of Broadcast Engineering
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    • v.26 no.4
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    • pp.419-428
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    • 2021
  • Shadow removal plays a key role for the pre-processing of image processing techniques such as object tracking and detection. With the advances of image recognition based on deep convolution neural networks, researches for shadow removal have been actively conducted. In this paper, we propose a novel method for shadow removal, which utilizes self attention distillation to extract semantic features. The proposed method gradually refines results of shadow detection, which are extracted from each layer of the proposed network, via top-down distillation. Specifically, the training procedure can be efficiently performed by learning the contextual information for shadow removal without shadow masks. Experimental results on various datasets show the effectiveness of the proposed method for shadow removal under real world environments.