• Title/Summary/Keyword: Conventional Visual Method

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Tree aging observation of XLPE by image processing (화상처리에 의한 XLPE의 트리열화관측)

  • 임장섭;김태성;길촌승
    • Electrical & Electronic Materials
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    • v.8 no.5
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    • pp.551-557
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    • 1995
  • For the observation of treeing, a visual measurement with an optical microscope has been used to explain breakdown mechanism in high-voltage systems. The conventional directed visual method of tree aging observation is difficult to measure in short time processing, and it is impossible to analyze on tree degradation area, progressed direction, tree pattern, etc. By using an image processing technique, the tree features which appear immediately after the tree initiation as well as changes in the configuration of the tree can be easily measured and observed than using the conventional visual methods. In this paper, we have developed a tree observating system by using image processing for tree growth, degradation area and other treeing progress. As an experimental result, it can be concluded that the image processing method is a more effective alternative than directed visual observation method. As a matter of fact, it is possible to record the image of tree propagation immediately after its first appearance and explain the characteristics of tree growth froth the computer processing image.

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Video Coding Method Using Visual Perception Model based on Motion Analysis (움직임 분석 기반의 시각인지 모델을 이용한 비디오 코딩 방법)

  • Oh, Hyung-Suk;Kim, Won-Ha
    • Journal of Broadcast Engineering
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    • v.17 no.2
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    • pp.223-236
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    • 2012
  • We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

Pre-filtering of Images Considering Human Visual Perception (시각특성을 고려한 영상의 전처리 필터링)

  • 권효섭;조남익
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.4
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    • pp.706-713
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    • 1997
  • In this paper, we propose a band stop filter(BSF) for reducing drag-like effect of the low pass filter(LPF), a block by block adaptive filtering method, and a motion adaptive filtering method, which show better results in terms of PSNR or human visual perception compared to the conventional method using LPF. The BSF improves the draglike effects of the low pass filter by passing temporal high frequency components of video sequences which correspond to objects with large motion. The proposed adaptive methods also improve the conventional adaptive filtering by modifying the conventional algorithm and applying the algorithms for small blocks. The simulation results show that the proposed filtering methods show better results in terms of PSNR and subjective tests in most cases. Also in case of block by block adaptive filtering, it is verified that the application of the algorithm for smaller block gives better results.

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A New Feature-Based Visual SLAM Using Multi-Channel Dynamic Object Estimation (다중 채널 동적 객체 정보 추정을 통한 특징점 기반 Visual SLAM)

  • Geunhyeong Park;HyungGi Jo
    • IEMEK Journal of Embedded Systems and Applications
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    • v.19 no.1
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    • pp.65-71
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    • 2024
  • An indirect visual SLAM takes raw image data and exploits geometric information such as key-points and line edges. Due to various environmental changes, SLAM performance may decrease. The main problem is caused by dynamic objects especially in highly crowded environments. In this paper, we propose a robust feature-based visual SLAM, building on ORB-SLAM, via multi-channel dynamic objects estimation. An optical flow and deep learning-based object detection algorithm each estimate different types of dynamic object information. Proposed method incorporates two dynamic object information and creates multi-channel dynamic masks. In this method, information on actually moving dynamic objects and potential dynamic objects can be obtained. Finally, dynamic objects included in the masks are removed in feature extraction part. As a results, proposed method can obtain more precise camera poses. The superiority of our ORB-SLAM was verified to compared with conventional ORB-SLAM by the experiment using KITTI odometry dataset.

Robust Position Tracking for Position-Based Visual Servoing and Its Application to Dual-Arm Task (위치기반 비주얼 서보잉을 위한 견실한 위치 추적 및 양팔 로봇의 조작작업에의 응용)

  • Kim, Chan-O;Choi, Sung;Cheong, Joo-No;Yang, Gwang-Woong;Kim, Hong-Seo
    • The Journal of Korea Robotics Society
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    • v.2 no.2
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    • pp.129-136
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    • 2007
  • This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

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Visual Feature Extraction Technique for Content-Based Image Retrieval

  • Park, Won-Bae;Song, Young-Jun;Kwon, Heak-Bong;Ahn, Jae-Hyeong
    • Journal of Korea Multimedia Society
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    • v.7 no.12
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    • pp.1671-1679
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    • 2004
  • This study has proposed visual-feature extraction methods for each band in wavelet domain with both spatial frequency features and multi resolution features. In addition, it has brought forward similarity measurement method using fuzzy theory and new color feature expression method taking advantage of the frequency of the same color after color quantization for reducing quantization error, a disadvantage of the existing color histogram intersection method. Experiments are performed on a database containing 1,000 color images. The proposed method gives better performance than the conventional method in both objective and subjective performance evaluation.

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A Study on Visual Emotion Classification using Balanced Data Augmentation (균형 잡힌 데이터 증강 기반 영상 감정 분류에 관한 연구)

  • Jeong, Chi Yoon;Kim, Mooseop
    • Journal of Korea Multimedia Society
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    • v.24 no.7
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    • pp.880-889
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    • 2021
  • In everyday life, recognizing people's emotions from their frames is essential and is a popular research domain in the area of computer vision. Visual emotion has a severe class imbalance in which most of the data are distributed in specific categories. The existing methods do not consider class imbalance and used accuracy as the performance metric, which is not suitable for evaluating the performance of the imbalanced dataset. Therefore, we proposed a method for recognizing visual emotion using balanced data augmentation to address the class imbalance. The proposed method generates a balanced dataset by adopting the random over-sampling and image transformation methods. Also, the proposed method uses the Focal loss as a loss function, which can mitigate the class imbalance by down weighting the well-classified samples. EfficientNet, which is the state-of-the-art method for image classification is used to recognize visual emotion. We compare the performance of the proposed method with that of conventional methods by using a public dataset. The experimental results show that the proposed method increases the F1 score by 40% compared with the method without data augmentation, mitigating class imbalance without loss of classification accuracy.

Development of Probability Based Defect Verification Algorithm for Automatic Visual Inspection (자동외관검사를 위한 확률기반 불량 확인 알고리즘 개발)

  • Kim, Youngheub;Ryu, Sun-Joong
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.2
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    • pp.1-8
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    • 2017
  • The visual inspection of electronic parts consists of two steps: automatic visual inspection and verification inspection. In the stage of a verification inspection, the human inspector sequentially inspects all the areas which detected in the automatic inspection. In this study, we propose an algorithm to determine the order of verification inspection by Bayes inference well known in the field of machine learning. This is a method of prioritizing a region estimated to have a high probability of defect using experience data of past inspection. This algorithm was applied to the visual inspection of ultraviolet filters to verify its effectiveness. As a result of the comparison experiment, it was confirmed that the verification inspection can be completed 30% of the conventional method by adapting proposed algorithm.

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A Comparison of Patient-Controlled Analgesia and Conventional Intramuscular Opioid Regimen in Relation to their Post-Operative Pain Control and Side Effects (수술후 통증 관리의 Patient-Controlled Analgesia와 마약류의 전통적인 근육내 주사와의 비교)

  • Lee, Sang-Hun;Lee, Jin-Kyung;Lee, Kyn-Chang;Woo, Nam-Sik;Lee, Ye-Chul
    • The Korean Journal of Pain
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    • v.6 no.1
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    • pp.55-59
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    • 1993
  • Using a visual analogue scale, we compare the effect of patient-controlled analgesia and conventional intramuscular opioid regimen in 68 patients undergoing lower abdominal or gynecological surgery. We also recorded the incidence of side effects. We checked visual analogue scale 4 hours interval for 30 cases managed by patient-controlled analgesia and 38 cases of conventional intramuscular opioid group managed by obstetrician. We maintained fentanyl $0.33{\mu}g/kg/hr$ and set self administrable bolus dose $5.0{\mu}g$(lockout interval: 15 min) in patient-controlled analgesia group. Conventional intramuscular bolus injection group were administered meperidine 50 mg for 4 hour interval. Mean visual analogue scale scores obtained by patient-controlled analgesia group and intramuscular bolus injection group were $2.49{\pm}0.67$ and $4.53{\pm}1.28$(p<0.05). Side effects such as; no significant incidence of respiratory depression, urinary retention, postural hypotension, nausea, vomiting and pruritus were developed by either group. These results suggest that patient-controlled analgesia was more effective method compared with conventional intraumuscular opioid injection regimen for post-operative pain management.

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An Adaptive Block Truncation Coding Using Human Visual System (인간시각 체계를 이용한 적응 구획 절단 부호화)

  • 신용달;이봉락;이건일
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.12
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    • pp.67-72
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    • 1993
  • An adaptive block truncation coding(BTC) using human visual system(HVS) is proposed. To reduce visible blocking effect at sensitive area in HVS. a new category classification coefficient is proposed. The categroy classification coefficient was derived by combining the modified HVS and standard deviation. By computer simulations, we showed that the proposed method reduced blocking effect at low bit rate coding more than the conventional Hui's method.

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