• Journal of the Semiconductor & Display Technology
• /
• v.22 no.4
• /
• pp.48-52
• /
• 2023

From the past to the present, banners are consistently used as effective advertising means. In the case of Korea, there are frequent situations in which hidden advertisements are installed. As a result, such hidden advertisement materials may damage urban aesthetics and moreover, incur unnecessary manpower consumption and waste of money. The proposed method classifies the detected banners into good banner and bad banner. The classification results are based on whether the relevant banners are installed in compliance with legal guidelines. In the process, YOLO and Open Computer Vision library are used to determine from various perspectives whether banners in CCTV images comply with the guidelines. YOLO is used to detect the banner area in CCTV images, and OpenCV is used to detect the color values in the area for color comparison. If a banner is detected in the video, the proposed method calculates the location of the banner and the distance from the designated bulletin to determine whether it was installed within the designated location, and then compares whether the color used in the banner is complied with local government guidelines.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.959-979
• /
• 2024

Rice pest identification is essential in modern agriculture for the health of rice crops. As global rice consumption rises, yields and quality must be maintained. Various methodologies were employed to identify pests, encompassing sensor-based technologies, deep learning, and remote sensing models. Visual inspection by professionals and farmers remains essential, but integrating technology such as satellites, IoT-based sensors, and drones enhances efficiency and accuracy. A computer vision system processes images to detect pests automatically. It gives real-time data for proactive and targeted pest management. With this motive in mind, this research provides a novel farmland fertility algorithm with a deep learning-based automated rice pest detection and classification (FFADL-ARPDC) technique. The FFADL-ARPDC approach classifies rice pests from rice plant images. Before processing, FFADL-ARPDC removes noise and enhances contrast using bilateral filtering (BF). Additionally, rice crop images are processed using the NASNetLarge deep learning architecture to extract image features. The FFA is used for hyperparameter tweaking to optimise the model performance of the NASNetLarge, which aids in enhancing classification performance. Using an Elman recurrent neural network (ERNN), the model accurately categorises 14 types of pests. The FFADL-ARPDC approach is thoroughly evaluated using a benchmark dataset available in the public repository. With an accuracy of 97.58, the FFADL-ARPDC model exceeds existing pest detection methods.

• Journal of the Korean Society of Safety
• /
• v.39 no.1
• /
• pp.27-32
• /
• 2024

This study analyzed cases of hydrogen (H₂) and natural gas (CH₄) leakage from a hydrogen-blended natural gas pipeline to determine a range of leakage characteristics, including leakage type, pipe material, pipe diameter, pressure, and damage size. Based on the results of this analysis, five hydrogen-blended natural gas leakage scenarios were selected. The national vision for a carbon-neutral society by 2050 is a very important strategic objective and promotes environmentally sustainable economic development in the age of the climate crisis. Accordingly, zero-carbon and low-carbon policies are being promoted in various fields, including energy production, consumption, and industrial processes. Hydrogen-blended natural gas is eco-friendly and is considered an important step towards carbon neutrality, with various countries including the United States and several European countries conducting empirical research to further investigate its potential. In Korea, a national research project commenced in April 2023 to verify and demonstrate the life cycle safety of blending hydrogen into the natural gas network. The results of this study will provide important data for the analysis of the damage impacts caused by the leakage of hydrogen-blended natural gas, such as the diffusion of gas clouds, fires, and gas explosions.

• Environmental and Resource Economics Review
• /
• v.16 no.2
• /
• pp.275-311
• /
• 2007

Hydrogen energy is emphasized as a substitutable energy of carbon-based energy system in the future, since it is non-depletable and clean energy. Long term vision of Korean government on the national energy system is to promote hydrogen energy by 15% of final energy demand until 2040. This study analyzes economic impacts of hydrogen energy development employing a dynamic CGE model for Korea. Frontier technology such as hydrogen energy is featured as slow diffusion at the initial stage due to the learning effect and energy complementarity. Without government intervention, hydrogen energy would be produced upto 6.5% of final energy demand until 2040. However, if government subsidizes sales price of hydrogen energy by 10%, 20%, and 30%, share of hydrogen energy would increase 9.2%, 15.2%, and 37.7% of final energy demand. This result shows that the slow diffusion problem of hydrogen energy as frontier technology could be figured out by market incentive policy. On the other hand, production levels of transportation sector would increase while growth rate of oil and electricity sectors would decline. Household consumption would be affected negatively since increase of consumption due to the price decrease would be overwhelmed by income reduction owing to the increase of tax. Overall, GDP would not decrease or increase significantly since total production, investment, and export would increase even if household consumption declines.

• Journal of Korean Ophthalmic Optics Society
• /
• v.9 no.2
• /
• pp.257-267
• /
• 2004

Our study investigated the association between solvent exposure and acquired color vision loss using the Lanthony D-15 desaturated panel in petrochemical industry. Since neurotoxic effects associated with chronic solvent exposure, subjects with more than 6 months of exposure were included. Exposure assesment was estimated mean, maximum and cumulative 8hr TWA from individual 8-hour sampling. Exposure status were classified into two groups, occupationally exposed group to solvent and a non-exposed group. The results showed that CCI was positively related for age. According to the results of qualitative analysis, there was no significant difference in the prevalence of specific Type of dyschromatopsia the two examined group. However, the prevalence showed a higher proportion of dyschromatopsia to solvent exposure. It was affect with acquired dyschromatopsia(Type II, III and Complex) in exposed worker group(5.9%,7.86%,14.99%, respectively) than in the nonexposed group(6.16%,7.55%,13.71%, respectively). After each variable was adjusted for age, alcohol and tobacco consumption, a relationship between acquired dyschromatopsia and exposure showed an increase in the Odds ratio as compared to the nonexposed group at only left. The results showed that acquired dyschromatopsia was positively related to age (p<0.001). The results showed that solvent exposure, although not significant, could cause the acquired dyschromatopsia and visual system can serve important information on early neurotoxic effects in generally. Therefore, we need to concerns about eye health in workers.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.3
• /
• pp.12-19
• /
• 2008

Detection of a number plate consists of three stages; division of a number plate, extraction of each character from the plate, recognition of the characters. Among of these three states, division stage of a number plate is the most important part and also the most time-consuming state. This paper suggests an effective region extraction method of a number plate for various images obtained from unmanned inspection systems of illegal parking violation, especially when we have to consider the diverse surrounding environments of roads. Our approaching method detects each region by investigating the characteristics in changes of brightness and intensity between the background part and character part, and the characteristics on character parts such as the sizes, heights, widths, and distance in between two characters. The method also divides a number plate into different types of the plate. This research can solve the number plate region detection failure problems caused by plate edge damages not only for Korean domestic number plates but also for new European style number plates. The method also reduces the time consumption by processing the detection in real-time, therefore, it can be used as a practical solution.

• 재활복지
• /
• v.21 no.3
• /
• pp.129-146
• /
• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.5
• /
• pp.538-547
• /
• 2001

Currently, 2D real-time image coding techniques had great developments and many related products were commercially developed. However, these techniques lack the capability of handling 3D actuality, occurred by the advent of virtual reality, because they handle only the temporal transmission for 2D image. Besides, many 3D virtual reality researches have been studied in computer graphics. Since the graphical researches were limited to the application of artificial models, the 3D actuality for real scene images could not be managed also. Therefore, a new 3D model extraction method based on stereo vision, that can deal with real scene virtual reality, is proposed in this paper. The proposed method adapted a compact genetic algorithm using population-based incremental learning (PBIL) to matching environments, in order to reduce memory consumption and computational time of conventional genetic algorithms. Since the PBIL used a probability vector and competitive learning, the matching algorithm became simple and the computation load was considerably reduced. Moreover, the matching quality was superior than conventional methods. Even if the characteristics of images are changed, stable outputs were obtained without the modification of the matching algorithm.

• Trans-
• /
• v.6
• /
• pp.79-95
• /
• 2019

The advent of the handheld camera has dramatically transformed film production and consumption in countless ways. French director and theorist, Alexandre Astruc focuses on the development of 16mm camera and foretell film will be used as a tool to realize the personal vision of the author like other art. As proof of his claim French New Wave and Cinéma vérité create the film with handheld camera on the real location to capture new reality. Their films are distinguished itself from other films made by conventional Hollywood studios. Similarly, John Cassavetes in the United States began to focus on the handheld camera. Since then the handheld camera has become one of the popular shooting methods. Especially, handheld camera are noted for their agile movement and mobility as a way to capture various realities. However, with the advances in technology, lighter cameras and higher resolution have changed in different ways. The technology is neutral, one shooting method does not serve for one philosophy or ism. At one time, handheld shooting is now used as not only a means to capture the real world but also a tool to mimic a realistic feeling.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.1
• /
• pp.129-134
• /
• 2010

Low-carbon Green Growth is highlighted as the main political issue from in and outof Korea. Recently Korean government announced the vision for low-carbon green growth. Considering this as a starting point the carbon emission estimation has become an important factor in the city planning. In order to realize the carbon reduction planning, this research was focused on the trend analyzes between the carbon exhaust estimation as well as the land use change for the past 40 years in Jinju. The image processing data of past aerial photography and the land suitability assessment databases were used to collect the useful information's for the land trend analysis for 40 years. As the results, the land use changes by new residential developments have led to increase the carbon emissions and population concentration rapidly. The urban management planning for low carbon and green growth should consider carbon emissions by population growth derived from land use change. Further research need to estimate the accurate carbon exhaust using relationship model with fuel consumption, carbon estimation, and land use.