• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.74-79
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• 2004

The effects of change in injection pressure on spray structure have been investigated in high temperature and pressure field. To analyze the structure of evaporative diesel spray is important in speculation of mixture formation process. Also emissions of diesel engines can be controlled by the analyzed results. Therefore, this study examines the evaporating spray structure by using a constant volume vessel. The injection pressure is selected as the experimental parameter, is changed from 72 MPa to 112 MPa with a high pressure injection system(ECD-U2). The PIV(Particle Image Velocimetry) technique was used to capture flow variation of the evaporative diesel spray. A study on the mixture formation process of diesel spray was executed by the results of flow analysis in this study. Consequentially the large-scale vortex flow could be found in downstream spray and the formed vortex governs the mixture formation process in diesel spray.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.103-104
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• 2018

치과의 모든 정보뿐만 아니라, 공급 사슬관리, 고객의 정보까지 포함하여 통합적으로 관리해야 하므로 특정한 기능을 수행하는 기술개발의 범위보다는 환자의 구강 정보의 원활한 처리를 위한 서버 구축 및 영상의 질 및 촬영의 용이함을 위한 실시간 스트리밍 기술이 필요하다. 영상정보 판독을 통해 치주염의 위험을 보고 환자들의 치과 방문을 유도하는 것이 치료 적기를 놓치지 않기 위해 반드시 필요하다. 이 논문에서는 구강 질환 예방 및 관리를 위한 스트리밍 기반 모바일 촬영 시스템을 제안한다. 특히 환자 자신이 구강 내의 이미지를 클라이언트 앱을 통해 환부를 직접 확인해 가며 조절하여 촬영가능하도록 스트리밍 기법을 제시하며, 이 과정에서 프레임의 버퍼링 및 딜레이 현상을 사용자의 개입없이 자동 조절하는 기능을 제안한다.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.458-465
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• 2018

Purpose: Concrete track that affects on railway safety can detect cracks using image processing technique. However, since a condition of concrete track and surface noisy are obstructed to detect cracks, there is a need for a way to remove them effectively. Method: In this study, we proposed an image processing to detect cracks effectively for Korean railway and verified its performance through experiment. We developed image acquisition system for capture a railway concrete track and acquired railway concrete track images, randomly selected 2000 images and detected cracks in the image process using proposed Gabor Filter Bank methods. Results: As a result, 94% of detection rate are matched to the actual cracks in same quality and format railway concrete track image. Conclution: The crack detection method using Garbor Filter Bank was confirmed to be effective for crack image including noise in the Korean railway concrete track. This system is expected to become an automated maintenance system in the existing human-centered railway industry.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.881-886
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• 2013

Even though a multi-view camera system is able to capture multiple images at different viewpoints, the color distributions of captured multi-view images can be inconsistent. This problem decreases the quality of multi-view images and the performance of post-image processes. In this paper, we propose an improved polynomial model for effectively correcting the color inconsistency problem. This algorithm is fully automatic without any pre-process and considers occlusion regions of the multi-view image. We use the 5th order polynomial model to define a relative mapping curve between reference and source views. Sometimes the estimated curve is seriously distorted if the dynamic range of extracted correspondences is quite low. Therefore we additionally estimate the first order polynomial model for the bottom and top regions of the dynamic range. Afterwards, colors of the source view are modified via these models. The proposed algorithm shows the good subjective results and has better objective quality than the conventional color correction algorithms.

• Journal of Korean Neurosurgical Society
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• v.39 no.6
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• pp.471-474
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• 2006

Objective : Neuroimaging data are of paramount importance in making correct diagnosis. We herein evaluate the clinical usefulness of image transfer using cellular phones to facilitate neurological diagnosis and decision-making. Methods : Selected images from CT, MRI scans, and plain films obtained from 50 neurosurgical patients were transferred by cellular phones. A cellular phone with a built-in 1,300,000-pixel digital camera was used to capture and send the images. A cellular phone with a 262,000 color thin-film transistor liquid crystal display was used to receive the images. Communication between both cellular phones was operated by the same wireless protocol and the same wireless internet service. We compared the concordance of diagnoses and treatment plans between a house staff who could review full-scale original films and a consultant who could only review transferred images. These finding were later analyzed by a third observer. Results : The mean time of complete transfer was $2{\sim}3\;minutes$. The quality of all images received was good enough to make precise diagnosis and to select treatment options. Transferred images were helpful in making correct diagnosis and decision making in 49/50 [98%] cases. Discordant result was caused in one patient by improper selection of images by the house staff. Conclusion : The cellular phone system was useful for image transfer and delivery patient's information, leading to earlier diagnosis and initiation of treatment. This usefulness was due to sufficient resolution of the built-in camera and the TFT-LCD, the user-friendly features of the devices, and their low cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.398-403
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• 2006

In this paper, we describe a fuzzy threshold selection technique for feature extraction in digital color images. this is achieved by the formulation a fuzzy inference system that evaluates threshold for feature configurations. The system uses two fuzzy measures. They capture desirable characteristics of features such as dependency of local intensity and continuity in an image. We give a graphical description of a nonlinear sketch feature extraction filter and design the fuzzy inference system in terms of the characteristics of the feature. Through the design, we provide selection method on the choice of a threshold to achieve certain characteristics of the extracted features. Experimental results show the usefulness of our fuzzy threshold inference approach which is able to extract features without human intervention.

• Journal of the Optical Society of Korea
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• v.11 no.1
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• pp.18-25
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• 2007

We present an ultrahigh-resolution full-field optical coherence tomography (FF-OCT) implemented with a white-light interference microscope and a detector array as an alternative OCT technique. The use of detector array allows the capture of two-dimensional en-face images in parallel without taking any lateral scanning process. The phase shifting interferometric technique with the sinusoidal phase modulation (SPM) is utilized to get the demodulated OCT images. The configuration of the system and the resolution of the obtained image are presented. The topographic images, taken with the implemented system, of a coin, an integrated circuit chip, and the tomographic images of an onion epithelium are demonstrated also. Axial and lateral spatial resolution of ${\sim}1.0{\mu}m$ and ${\sim}2.0{\mu}m$ are achieved with the system respectively.