• Title/Summary/Keyword: Area Detection

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A Numerical Study on Smoke Behavior of Fishing Vessel Engine Room (어선 기관실의 연기 거동에 관한 수치해석 연구)

  • JANG, Ho-Sung;JI, Sang-Won
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.5
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    • pp.683-690
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    • 2021
  • The ventilation system of the engine room of a ship is generally installed to supply the combustion air necessary for the internal combustion engine and to remove the heat source generated in the engine room, and it must satisfy the international standard (ISO 8861) for the design conditions and calculation standards for the ventilation of the ship engine room. The response delay of the ventilation system including the fire detector is affected by the airflow formed inside the area and the location of the fire detector. In this study, to improve the initial fire detection response speed of a fire detector installed on a fishing vessel and to maintain the sensitivity of the installed detector, the smoke behavior was simulated using the air flow field inside the engine room, the amount of combustion air in the internal combustion engine, and the internal pressure of the engine room as variables. Analysis of the simulation results showed that reducing the flow rate in the air flow field and increasing the vortex by reducing the internal pressure of the engine room and installing a smoke curtain would accelerate the rise of the ceiling of the smoke component and improve the smoke detector response speed and ventilation system.

Feasibility Study on FSIM Index to Evaluate SAR Image Co-registration Accuracy (SAR 영상 정합 정확도 평가를 위한 FSIM 인자 활용 가능성)

  • Kim, Sang-Wan;Lee, Dongjun
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.847-859
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    • 2021
  • Recently, as the number of high-resolution satellite SAR images increases, the demand for precise matching of SAR imagesin change detection and image fusion is consistently increasing. RMSE (Root Mean Square Error) values using GCPs (Ground Control Points) selected by analysts have been widely used for quantitative evaluation of image registration results, while it is difficult to find an approach for automatically measuring the registration accuracy. In this study, a feasibility analysis was conducted on using the FSIM (Feature Similarity) index as a measure to evaluate the registration accuracy. TerraSAR-X (TSX) staring spotlight data collected from various incidence angles and orbit directions were used for the analysis. FSIM was almost independent on the spatial resolution of the SAR image. Using a single SAR image, the FSIM with respect to registration errors was analyzed, then use it to compare with the value estimated from TSX data with different imaging geometry. FSIM index slightly decreased due to the differencesin imaging geometry such as different look angles, different orbit tracks. As the result of analyzing the FSIM value by land cover type, the change in the FSIM index according to the co-registration error was most evident in the urban area. Therefore, the FSIM index calculated in the urban was mostsuitable for determining the accuracy of image registration. It islikely that the FSIM index has sufficient potential to be used as an index for the co-registration accuracy of SAR image.

Convergence CCTV camera embedded with Deep Learning SW technology (딥러닝 SW 기술을 이용한 임베디드형 융합 CCTV 카메라)

  • Son, Kyong-Sik;Kim, Jong-Won;Lim, Jae-Hyun
    • Journal of the Korea Convergence Society
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    • v.10 no.1
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    • pp.103-113
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    • 2019
  • License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

Analysis of size distribution of riverbed gravel through digital image processing (영상 처리에 의한 하상자갈의 입도분포 분석)

  • Yu, Kwonkyu;Cho, Woosung
    • Journal of Korea Water Resources Association
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    • v.52 no.7
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    • pp.493-503
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    • 2019
  • This study presents a new method of estimating the size distribution of river bed gravel through image processing. The analysis was done in two steps; first the individual grain images were analyzed and then the grain particle segmentation of river-bed images were processed. In the first part of the analysis, the relationships (long axes, intermediate axes and projective areas) between grain features from images and those measured were compared. For this analysis, 240 gravel particles were collected at three river stations. All particles were measured with vernier calipers and weighed with scales. The measured data showed that river gravel had shape factors of 0.514~0.585. It was found that the weight of gravel had a stronger correlation with the projective areas than the long or intermediate axes. Using these results, we were able to establish an area-weight formula. In the second step, we calculated the projective areas of the river-bed gravels by detecting their edge lines using the ImageJ program. The projective areas of the gravels were converted to the grain-size distribution using the formula previously established. The proposed method was applied to 3 small- and medium- sized rivers in Korea. Comparisons of the analyzed size distributions with those measured showed that the proposed method could estimate the median diameter within a fair error range. However, the estimated distributions showed a slight deviation from the observed value, which is something that needs improvement in the future.

Outbreak of Fire Blight of Apple and Pear and Its Characteristics in Korea in 2019 (2019년 국내 사과와 배 화상병 대발생과 그 특징)

  • Ham, Hyeonheui;Lee, Kyong Jae;Hong, Seong Jun;Kong, Hyun Gi;Lee, Mi-Hyun;Kim, Hyun-Ran;Lee, Yong Hwan
    • Research in Plant Disease
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    • v.26 no.4
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    • pp.239-249
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    • 2020
  • To find out the cause of the fire blight outbreak in apples and pears of Korea in 2019, we investigated disease appearing situation of thirty fire blight infected orchards, and interviewed farmers to determine the cultivation characteristics. Fire blight occurred mostly in orchards that had infected more than 2 years before. The cause of this were as follows: farmers did not know the symptoms of the disease properly. It is presumed that it has spread from the first occurrence to the surrounding orchards by flower-visiting insects or farmers and to a short distance or a long distance by the same cultivator or co-farmer. These series of processes repeated in the newly spreading area, and then disease reports increased as farmers became aware of fire blight. To minimize the spread of fire blight in Korea, it suggested that thorough education of farmers for early diagnosis and quantitative detection technology that can diagnose even in no symptom showing plants. And chemical or biological spraying systems suitable for domestic cultivation methods, which are producing large fruits, and molecular epidemiological studies of pathogens.

Comparison of Multi-angle TerraSAR-X Staring Mode Image Registration Method through Coarse to Fine Step (Coarse to Fine 단계를 통한 TerraSAR-X Staring Mode 다중 관측각 영상 정합기법 비교 분석)

  • Lee, Dongjun;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.475-491
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    • 2021
  • With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

A Study on Field Compost Detection by Using Unmanned AerialVehicle Image and Semantic Segmentation Technique based Deep Learning (무인항공기 영상과 딥러닝 기반의 의미론적 분할 기법을 활용한 야적퇴비 탐지 연구)

  • Kim, Na-Kyeong;Park, Mi-So;Jeong, Min-Ji;Hwang, Do-Hyun;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.367-378
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    • 2021
  • Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

An Efficient Method of Forensics Evidence Collection at the Time of Infringement Occurrence (호스트 침해 발생 시점에서의 효율적 Forensics 증거 자료 수집 방안)

  • Choi Yoon-Ho;Park Jong-Ho;Kim Sang-Kon;Kang Yu;Choe Jin-Gi;Moon Ho-Gun;Rhee Myung-Su;Seo Seung-Woo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.16 no.4
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    • pp.69-81
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    • 2006
  • The Computer Forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. Many researches about Computer Forensics have been done so far. But those researches have focussed on how to collect the forensic evidence for both analysis and poofs after receiving the intrusion or infringement reports of hosts from computer users or network administrators. In this paper, we describe how to collect the forensic evidence of good quality from observable and protective hosts at the time of infringement occurrence by malicious users. By correlating the event logs of Intrusion Detection Systems(IDSes) and hosts with the configuration information of hosts periodically, we calculate the value of infringement severity that implies the real infringement possibility of the hosts. Based on this severity value, we selectively collect the evidence for proofs at the time of infringement occurrence. As a result, we show that we can minimize the information damage of the evidence for both analysis and proofs, and reduce the amount of data which are used to analyze the degree of infringement severity.

Quality, Safety and Sensory Characteristics of Plum Jangachi Produced using Automatic Plum Sarcocarp Separator (매실 과육 자동 분리기를 이용하여 제조한 매실장아찌의 품질, 안전성 및 관능특성)

  • Lee, Sang-Yoon;Park, Woo-Jun;Kim, Hyuck-Joo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.368-377
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    • 2021
  • Plum is a typical fruit that is consumed processed rather than raw. In this study, we manufactured one of the processed foods, viz., plum Jangachi. In this process, the manpower-dependent seed separation and flesh cutting operations were automated by mechanizing, thereby altering the manufacturing process. Quality and Safety were assessed through microbial evaluation, analysis of color, and detection of preservatives in the plum Jangachi. Preference factors were identified through sensual evaluation. When compared with other plum Jangachi currently available in the market, our product was determined to contain 2.7±0.1 Log CFU/g total aerobic bacteria, which is slightly higher than the average of other products. This was not surprising, as the figures are due to the inherent characteristics, which were determined to be lower as compared to other commercial plum Jangachi. Other coliforms, tar dyes, and preservatives were undetected, thereby conferring satisfactory Quality and Safety. In general, there was no statistical difference in the sensual evaluation and appearance; overall, our product received better feedbacks than products on the market. Taken together, our results provide a foundation for applying the mechanization of plum-processed foods, thereby promoting the local economy in the main production area, and overall characteristics obtained are regarded sufficient in terms of market competitiveness.

Enzyme-Free Glucose Sensing with Polyaniline-Decorated Flexible CNT Fiber Electrode (Polyaniline을 이용한 CNT fiber 유연 전극 기반의 비효소적 글루코스 검출)

  • Song, Min-Jung
    • Korean Chemical Engineering Research
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    • v.60 no.1
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    • pp.1-6
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    • 2022
  • As the demand for wearable devices increases, many studies have been studied on the development of flexible electrode materials recently. In particular, the development of high-performance flexible electrode materials is very important for wearable sensors for healthcare because it is necessary to continuously monitor and accurately detect body information such as body temperature, heart rate, blood glucose, and oxygen concentration in real time. In this study, we fabricated the nonenzymatic glucose sensor based on polyaniline/carbon nanotube fiber (PANI/CNT fiber) electrode. PANI layer was synthesized on the flexible CNT fiber electrode through electrochemical polymerization process in order to improve the performance of a flexible CNT fiber based electrode material. Surface morphology of the PANI/CNT fiber electrode was observed by scanning electron microscopy. And its electrochemical characteristics were investigated by chronoamperometry, cyclic voltammetry, electrochemical impedance spectroscopy. Compared to bare CNT fiber electrode, this PANI/CNT fiber electrode exhibited small electron transfer resistance, low peak separation potential and large surface area, resulting in enhanced sensing properties for glucose such as wide linear range (0.024~0.39 and 1.56~50 mM), high sensitivity (52.91 and 2.24 ㎂/mM·cm2), low detection limit (2 μM) and good selectivity. Therefore, it is expected that it will be possible to develop high performance CNT fiber based flexible electrode materials using various nanomaterials.