• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.628-637
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• 2017

The automobile industry has developed Advanced Driver Assistance Systems (ADASs) to prevent traffic accidents and reduce the burden for drivers. One example is the Lane Keeping Assistance System (LKAS), which was developed for automotive vehicle systems for safety and better driving. The main system of the LKAS supports the driver while maintaining the vehicle within a lane. LKAS uses a radar sensor and camera sensor to collect information about the vehicle's position in the lane and send commands to the actuator to influence the lateral movement of the vehicle if necessary. Recently, vehicles equipped with LKAS have become commercially available. Test procedures for international LKAS evaluation are being discussed and developed by international committees, such as the International Organization for Standardization and United Nations Economic Commission for Europe. In Korea, an evaluation of LKASs for car safety is being planned by the Korean New Car Assessment Program. Therefore, test procedures should be developed for LKASs that are suitable for the domestic road environment while accommodating international standards. We developed a test scenario for LKASs and propose a formula for obtaining the target relative distance. To validate the methods, a series of experiments were conducted using commercially available vehicles equipped with LKAS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.246-252
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• 2020

Safety accidents have been reported due to falling accumulated snow from cables of cable-supported bridges. In addition to the direct damage caused by falling snow, secondary damage, such as traffic accidents, can occur. Various methods have been proposed to prevent these accidents, but there are still problems in safety and practicality. In this study, a cable robot type was selected as one of the active methods for removing accumulated snow on cables. An attempt was made to increase the climbing ability of the robot to improve the efficiency of snow removal. In addition, the available range of cable diameter for the robot can be adjusted flexibly to be applied to cables used in the field. A high-resolution camera was also installed to check the surface condition of the cable in real time to increase the utility, and be used as a cable inspection robot. A three-axis accelerometer and a tension conversion algorithm were added to measure the tension force of cables. To verify the performance, indoor and field experiments were conducted, and future improvements for the inspection robot were proposed.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.8-15
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• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• Asian Journal of Atmospheric Environment
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• v.9 no.2
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• pp.128-136
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• 2015

Sky View Factor (SVF) is one of the urban morfometri parameters that impact on the Urban Heat Island (UHI). SVF analisys was conducted in the city of Jakarta to investigate the relationship between urban temperature with urban morfometri. Jakarta City is the most populous city in the world that has a surrounding area $66,152km^2$ and the total population around 23 million people. The population of the city is the sixth highest in the world today. SVF measurements done by taking pictures at the six stations that have different morphological characteristics namely (1) the narrow streets Apartment Cempaka Mas (JS ITC), (2) the width of the road Apartment Cempaka Mas (JL ITC), (3) in front of Colleges Kanisius (DKK), (4) in front of office Journalist of Indonesia (DKWI), (5) Utan Kayu (UK), and (6) Tambun (TB). SVF value is obtained from the photgraphic image. Taking pictures at the location using a Nikon D90 camera with a Nikon Fisheye Nikkor 10.5 mm 1 : 2.8 G ED, further processed through a global mapper program. Therefore, the SVF derived from the six stations that vary 0.21 to 0.78. Temperature measurement is done during daylight hours from 06:00 am to 18:00 pm during the Western Part of Indonesia (WIB). Measurements performed at three different times, namely working days (HK) regular holidays (HCB) national holidays (HCN). The results showed that the highest average temperature of $33.32^{\circ}C$, occurring at UK station (SVF=0.45) at the time of HCB. Meanwhile, the average low temperature of $31.22^{\circ}C$ occurred at JLITC station (SVF=0.42). The two-time occurred on ordinary holidays. Maximum temperature of $38.4^{\circ}C$ occurred in Utan Kayu station (SFV=0.45) that occurred at 11.00 hrs, normal holidays. Furthermore minimum temperature 24.5 occurred at Tambun station (SVF=0.78) at 06.00 hrs in the morning at the usual holidays and national holidays. In general, the results showed that areas with large SVF has a lower temperature compared with areas with smaller SVF. Though, are not the only factors that matter, but this research may show that an increase in temperature in the city of Jakarta. Therefore, it is necessary to mitigate the serious from the government or society.

• Cartoon and Animation Studies
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• s.43
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• pp.343-362
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• 2016

The purpose of this study is to analyze the 'depth of the film image' and to discuss its aesthetic implications in the Wes Anderson's films. In this study, I have analysed his two recent representative films, (2014) and (2012). As a result, it is found that Wes Anderson created a symmetrical composition with the depth by placing symmetrically things on the Z axis or using one-point perspective. In general, symmetrical composition is a two-dimensional form. The symmetrical composition in these two films, however, has the depth perception. It gives a sense of the fantastic world, not the real world. Thus, it is the unique way of Wes Anderson's expressing the world of the fairy tale on his films. It is also found that he used the camera work, emphasizing the depth of the image. Through these devices, Wes Anderson has created his own sensational mise-en-scene for a storyline like a fairy tale.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.257-264
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• 2020

Vectorization is currently the main method in feature collection (extraction) during digital mapping using UAV-Photogrammetry. However, this method is time consuming and prone to gross elevation errors when extracted from a DSM (Digital Surface Model), because three-dimensional feature coordinates are vectorized separately: plane information from an orthophoto and height from a DSM. Consequently, the demand for stereo plotting method capable of acquiring three- dimensional spatial information simultaneously is increasing. However, this method requires an expensive equipment, a Digital Photogrammetry Workstation (DPW), and the technology itself is still incomplete. In this paper, we evaluated the accuracy of low-cost stereo plotting system, Menci's StereoCAD, by analyzing its three-dimensional spatial information acquisition. Images were taken with a FC 6310 camera mounted on a Phantom4 pro at a 90 m altitude with a Ground Sample Distance (GSD) of 3 cm. The accuracy analysis was performed by comparing differences in coordinates between the results from the ground survey and the stereo plotting at check points, and also at the corner points by layers. The results showed that the Root Mean Square Error (RMSE) at check points was 0.048 m for horizontal and 0.078 m for vertical coordinates, respectively, and for different layers, it ranged from 0.104 m to 0.127 m for horizontal and 0.086 m to 0.092 m for vertical coordinates, respectively. In conclusion, the results showed 1: 1,000 digital topographic map can be generated using a stereo plotting system with UAV images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.317-325
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• 2020

UAV (Unmanned Aerial Vehicle) photogrammetry has recently emerged as a means of obtaining highly precise and rapid spatial information due to its cost-effectiveness and high efficiency. However, current procedures or regulations for quantitative quality verification methods and certification processes for UAV-images are insufficient. In addition, the current verification method for image quality is not evaluated by an MTF (Modulation Transfer Function) analysis or edge response analysis, which can analyze the degree of contrast including image resolution, and only relies on the GSD (Ground Sample Distance) analysis. Therefore, in this study, the edge response analysis using a Slanted edge target was performed along with GSD analysis to confirm the necessity of analyzing edge response analysis in UAV-images quality analysis. Furthermore, a Matlab GUI-based software tool was developed to help streamline the edge response analysis. As a result, we confirmed the need for edge response analysis since the outputs of the edge response analysis from the same GSD had significantly different outcomes. Additionally, we found that the quality of the edge response analysis of UAV-images is proportional to the performance of the camera mounted on the UAV.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.31-43
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• 2014

A depth map is an important component for stereoscopic image generation. Since the depth map acquired from a depth camera has a low resolution, upsamling a low-resolution depth map to a high-resolution one has been studied past decades. Upsampling methods are evaluated by objective evaluation tools such as PSNR, Sharpness Degree, Blur Metric. As well, the subjective quality is compared using virtual views generated by DIBR (depth image based rendering). However, works on the analysis of the relation between depth map upsampling and stereoscopic images are relatively few. In this paper, we investigate the relationship between subjective evaluation of stereoscopic images and objective performance of upsampling methods using cross correlation and linear regression. Experimental results demonstrate that the correlation of edge PSNR and visual fatigue is the highest and the blur metric has lowest correlation. Further, from the linear regression, we found relative weights of objective measurements. Further we introduce a formulae that can estimate 3D performance of conventional or new upsampling methods.

• Atmosphere
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• v.21 no.2
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• pp.131-142
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• 2011

Spectral solar irradiances were observed using a visible and UV Multi-Filter Rotating Shadowband Radiometer on the rooftop of the Science Building at Yonsei University, Seoul ($37.57^{\circ}N$, $126.98^{\circ}E$, 86 m) during one year period in 2006. 1-min measurements of global(total) and diffuse solar irradiances over the solar zenith angle (SZA) ranges from $20^{\circ}$ to $70^{\circ}$ were used to examine the effects of clouds and total optical depth (TOD) on enhancing four solar irradiance components (broadband 395-955 nm, UV channel 304.5 nm, visible channel 495.2 nm, and infrared channel 869.2 nm) together with the sky camera images for the assessment of cloud conditions at the time of each measurement. The obtained clear-sky irradiance measurements were used for empirical model of clear-sky irradiance with the cosine of the solar zenith angle (SZA) as an independent variable. These developed models produce continuous estimates of global and diffuse solar irradiances for clear sky. Then, the clear-sky irradiances are used to estimate the effects of clouds and TOD on the enhancement of surface solar irradiance as a difference between the measured and the estimated clear-sky values. It was found that the enhancements occur at TODs less than 1.0 (i.e. transmissivity greater than 37%) when solar disk was not obscured or obscured by optically thin clouds. Although the TOD is less than 1.0, the probability of the occurrence for the enhancements shows 50~65% depending on four different solar radiation components with the low UV irradiance. The cumulus types such as stratoculmus and altoculumus were found to produce localized enhancement of broadband global solar irradiance of up to 36.0% at TOD of 0.43 under overcast skies (cloud cover 90%) when direct solar beam was unobstructed through the broken clouds. However, those same type clouds were found to attenuate up to 80% of the incoming global solar irradiance at TOD of about 7.0. The maximum global UV enhancement was only 3.8% which is much lower than those of other three solar components because of the light scattering efficiency of cloud drops. It was shown that the most of the enhancements occurred under cloud cover from 40 to 90%. The broadband global enhancement greater than 20% occurred for SZAs ranging from 28 to $62^{\circ}$. The broadband diffuse irradiance has been increased up to 467.8% (TOD 0.34) by clouds. In the case of channel 869.0 nm, the maximum diffuse enhancement was 609.5%. Thus, it is required to measure irradiance for various cloud conditions in order to obtain climatological values, to trace the differences among cloud types, and to eventually estimate the influence on solar irradiance by cloud characteristics.