• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korean Geosynthetics Society
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• v.19 no.4
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• pp.41-50
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• 2020

Since cracks in concrete structures expedite corrosion of reinforced concrete over a long period of time, regular on-site inspections are essential to ensure structural usability and prevent degradation. Most of the safety inspections of facilities rely on visual inspection with naked eye, so cost and time consuming are severe, and the reliability of results differs depending on the inspector. In this study, a portable measuring device that can be used for safety diagnosis and maintenance was developed as a device that measures the width and length of concrete cracks through image analysis of cracks photographed with a camera. This device captures the cracks found within a close distance (3 m), and accurately calculates the unit pixel size by laser distance measurement, and automatically calculates the crack length and width with the image processing algorithm developed in this study. In measurement results using the crack image applied to the experiment, the measurement of the length of a 0.3 mm crack within a distance of 3 m was possible with a range of about 10% error. The crack width showed a tendency to be overestimated by detecting surrounding pixels due to vibration and blurring effect during the binarization process, but it could be effectively corrected by applying the crack width reduction function.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.77-84
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• 2020

In this paper, we developed a damage evaluation technique that can determine the damage location of a long-sized structure such as a cable-stayed bridge, and verified the performance of the developed technique through experiments. The damage assessment method aims to extract data that can evaluate the damage of the structure without the undamage data and can determine the damage location only by analyzing the response data of the structure. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To evaluate the performance of the developed technique experimentally, cable damage experiments were conducted on model cable-stayed bridges. As a result, the damage assessment method considering variability automatically outputs the damageless data according to external force, and it is confirmed that the performance of extracting information that can determine the damage location of the cable through the analysis of the outputted damageless data and the measured damage data is shown.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.85-92
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• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean journal of applied entomology
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• v.29 no.3
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• pp.209-215
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• 1990

Some preliminary studies were conducted to find out whether the levee-burning could justifiable for the suppression of insect pests, particularly the smaller brown planthopper (Laodelphax striatellus F.). Density surveys on pests and their enemies (mostly spiders) were carried out upto the mid May at an experimental paddy field located in Suwon after of it's levee $(72\times1m)$ was burned on Feb. 20, 1987. Results were discussed in relation to density recovering of both pests and their possible enemies (spiders) and summarized as below. Not a single individual of any pest or enemy was found from the levee upto sometime after the levee-burning. Grasses started to grow more vigorously in burned ares than in unburned upto about 60 days after the burning. And densities of both pest and enemies grew higher in burned areas than in unburned from about 75 days after the burning (in Early may). It is suspected that all individuals of pests and enemies fond from the burned areas could have immigrated from the surrounding areas. If levee-burning was carried out in much wider areas, much longer time would be needed to recover the density of both pests and enemies to the center region of the burning. Wingless spiders would require even longer time than winged pest species to re-establish in the center region of the widely burned field. Pirata subpiraticus, the most abundant spider species in Korean paddy fields, starts to move about and searches for food at above $9^{\circ}C$ which is somewhat lower than the critical temperature for the pest species. Thus P. subpiraticus would require more food than other pest species early in the spring, and therefore, it would have lower probability to survive than pest species particularly in burned areas. Experiments for pest suppression with levee-burning would better be carried on in much wider areas, and its justification seems to be discussed after man other disciplines related to both pests and their natural enemies were throughly studied together with their density surveys. However, according to the present point of vie, the opinion that levee-burning is helpful for controlling pests which over winter on levee areas could not be justifiable.

• Progress in Medical Physics
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• v.24 no.2
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• pp.85-91
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• 2013

At present, megavoltage computed tomography (MVCT) is the only method used to correct the position of tomotherapy patients. MVCT produces extra radiation, in addition to the radiation used for treatment, and repositioning also takes up much of the total treatment time. To address these issues, we suggest the use of a video image-guided setup (VIGS) system for correcting the position of tomotherapy patients. We developed an in-house program to correct the exact position of patients using two orthogonal images obtained from two video cameras installed at $90^{\circ}$ and fastened inside the tomotherapy gantry. The system is programmed to make automatic registration possible with the use of edge detection of the user-defined region of interest (ROI). A head-and-neck patient is then simulated using a humanoid phantom. After taking the computed tomography (CT) image, tomotherapy planning is performed. To mimic a clinical treatment course, we used an immobilization device to position the phantom on the tomotherapy couch and, using MVCT, corrected its position to match the one captured when the treatment was planned. Video images of the corrected position were used as reference images for the VIGS system. First, the position was repeatedly corrected 10 times using MVCT, and based on the saved reference video image, the patient position was then corrected 10 times using the VIGS method. Thereafter, the results of the two correction methods were compared. The results demonstrated that patient positioning using a video-imaging method ($41.7{\pm}11.2$ seconds) significantly reduces the overall time of the MVCT method ($420{\pm}6$ seconds) (p<0.05). However, there was no meaningful difference in accuracy between the two methods (x=0.11 mm, y=0.27 mm, z=0.58 mm, p>0.05). Because VIGS provides a more accurate result and reduces the required time, compared with the MVCT method, it is expected to manage the overall tomotherapy treatment process more efficiently.

• Applied Biological Chemistry
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• v.16 no.2
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• pp.60-77
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• 1973

The non-enzymatic browning phenomenons of red ginseng were studied to identify these compounds which function as the factors for browning. The samples were classified into five divisions; Fresh ginseng, blanched ginseng, sun dried red ginseng, dehydrated red ginseng, and browning accelerated red ginseng respectively, and the various compounds in each of them were analyzed quantitatively and investigated the compounds which were thought to function for browning during the drying and the dehydration processes; the results were as follows. 1. The chemical compositions among five divisions did not show any difference except a) total and reducing sugars, b) total acids, c) water soluble extracts; a) and b) were decreased during the drying process, c) was decreased about 6-7% in red ginseng divisions. 2. Sixteen free amino acids; asp., thr., ser., glu., gly., ala., val., cys., met., ileu., leu., tyr., phe., lys., his., and arg, were identified in each division. Among them the arg, was extremly high. All of the essential amino acids were contained, while generally these amino acids were decreased in drying period and their rates were smaller in dehydrated red ginseng than in sun dried red ginseng. 3. Three kinds of sugars; fructose, glucose and sucrose were identified and other four kinds of unidentified sugars were seperated. The content of sucrose was 80% and all kind of sugars were generally less in red ginseng divisions than in the other two divisions. The decreasing rate of sngars was higher in the sun dried red ginseng than in the dehydrated red ginseng. Especially the decreasing rate of the reducing sugars was high as compared with that of sucrose. 4. Almost all the ascorbic acid was decomposed during the blanching whereas there could'nt be shown any change of the ascorbic acid content during the period of drying. 5. Eleven kinds of volatile acids; acetic acid, propionic acid, acrylic acid, iso-butyric acid, n-butyric acid, isovaleric acid, n-valeric acid, isoheptylic acid, n-heptylic acid, and an unknown volatile acid were identified. They showed a little decrease during the period of blanching perhaps on account of their volatility whereas they were increased in drying period. 6. Six kinds of non-volatile acids; citric acid, malic acid, ${\alpha}-ketoglutaric$ acid, succinic acid, pyruvic acid and glutaric acid were identified. The content of them were decreased during the drying procedures in red ginseng but only that of succinic acid was increased. 7. Three kinds of polyphenols; 3-caffeyl quinic acid, 4-caffeyl quinic acid, 5-caffeyl quinic acid and an unknown polyphenol were identified. The content of them showed considerable decrease during the drying procedures, especially in sun drying. 8. The intensity of the browning in each divisior was as follows; browning accelerated red ginseng> sun dried red ginseng> dehydrated red ginseng. 9. In the process of red ginseng preparation, a. certain relationship could be found between the decreasing rates of amino acids, reducing sugars, polyphenols and the intensity of browning. Therefore the browning phenomenon may be concluded that nonenzymatic browning reactions of the amino-carbonyl reaction and autoxidation of polyphenols are the most important processes, furthermore, as their reactions could be controlled it is thought to be possible to accelerate effectively browning within a relatively short period.