• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.463-466
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• 2010

In this paper, CCTV based fire surveillance system should aim to development. Advantages and Disadvantages analyzed of Existing sensor-based fire surveillance system and video-based fire surveillance system. To national support U-City, U-Home, U-Campus, etc, spread the ubiquitous environment appropriate to fire surveillance system model and a fire judgement technology. For this study, Microsoft LifeCam VX-1000 using through the capturing images and analyzed for apple and tomato, Finally we used H.264. The client uses the Linux OS with ARM9 S3C2440 board was manufactured, the client's role is passed to the server to processed capturing image. Client and the server is basically a 1:1 video communications. So to multiple receive to video multicast support will be a specification. Is fire surveillance system designed for multiple video communication. Video data from the RGB format to YUV format and transfer and fire detection for Y value. Y value is know movement data. The red color of the fire is determined to detect and calculate the value of Y at the fire continues to detect the movement of flame.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Korean Journal of Heritage: History & Science
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• v.52 no.1
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• pp.170-189
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• 2019

Sochi Heo Ryun (小癡 許鍊, 1808-1893) was a literary artist of Chinese paintings of the Southern School during the late Joseon dynasty and the founder of paintings in the literary artist's style of Jindo County in South Jeolla Province. He was also a professional literary artist who acquired both learning and painting techniques under Choui (a Zen priest) and Kim Jeong-hee's teachings. Heo Ryun's landscape paintings were influenced by Kim Jung -hee. However, his ink orchid paintings, which he began producing in his later years, were not related to the 'Ink Orchid Paintings of Chusa (秋史蘭)'. His ink orchid paintings as a whole drew attention as he followed the old methods but still used rough brush strokes . Ordinary orchids were drawn based on Confucian content. However, his Jebal (題跋) and seal (印章) contain not only Confucian characters but also Taoist and Buddhist meanings. Therefore, it is possible to guess his direction of life and his private world of suffering. Ryun's ink orchid paintings reflected a variety of philosophies and aesthetic sensibilities. He went through a process of stylistic change over time and formed an 'Ink Orchid Painted Thought' in later life. The main characteristic of Sochi's ink orchid paintings is that he formed his own special methods for orchid paintings by mimicking the Manuals of Paintings. He drew orchids with his fingers in the beginning. Then, Jeongseop, Lee Ha-eung, Cho Hee-ryong, and others developed an organic relationship with the painting style of ink orchid paintings. Then in later years, orchid paintings reached the point of 'Picture Painted Thought (寫意畵)'. The above consideration shows that ink orchid paintings, which he produced until the end of his life, were the beginning of his mental vision and will to realize the image of a literal artist.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.10-15
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• 2020

Ultraviolet rays, which have wavelengths smaller than 400 nm, are very harmful to the eyes. Recently, high-energy visible light was also revealed to be harmful to retinal cells. Therefore, polymer eyeglass lenses that can block UV and high-energy visible light are needed for eye health. In this study, high-refractive-index polymer eyeglass lens, n=1.67, were manufactured using the injection-mold method with the m-xylene diisocyanate monomer, 2,3-bis((2-mercaptoethyl)thio)-1-propanethiol monomer, benzotriazole UV absorber, release of alkyl phosphoric ester, dye mixture of CI solvent violet 13, and catalyst of dibutyltin dichloride mixture. A multi-layer anti-reflection coating was applied to manufactured polymer eyeglass lenses for both sides using an E-beam evaporation system. The optical properties of the manufactured lenses with the UV and high-energy visible light-blocking function were analyzed by UV-visible spectrophotometry. As a result, the polymer eyeglass lens with a UV absorber of 0.5 wt. % blocked 99% of UV and high-energy visible light shorter than 411 nm. The average transmittance of the polymer eyeglass lens with a UV absorber of 0.5wt.% was 97.9% in the range of 460 ~ 660 nm for photopic eye sensitivity higher than 10%. Therefore, clear image acquisition in photopic vision is possible.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.363-368
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• 2021

Ship engine rooms have improved automation systems owing to the advancement of technology. However, there are many variables at sea, such as wind, waves, vibration, and equipment aging, which cause loosening, cutting, and leakage, which are not measured by automated systems. There are cases in which only one engineer is available for patrolling. This entails many risk factors in the engine room, where rotating equipment is operating at high temperature and high pressure. When the engineer patrols, he uses his five senses, with particular high dependence on vision. We hereby present a preliminary study to implement an engine-room patrol robot that detects and informs the machine room while a robot patrols the engine room. Images of ship engine-room equipment were classified using a convolutional neural network (CNN). After constructing the image dataset of the ship engine room, the network was trained with a pre-trained CNN model. Classification performance of the trained model showed high reproducibility. Images were visualized with a class activation map. Although it cannot be generalized because the amount of data was limited, it is thought that if the data of each ship were learned through transfer learning, a model suitable for the characteristics of each ship could be constructed with little time and cost expenditure.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.5-25
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• 2022

The purpose of this study is to analyze the duties and competencies of the teacher librarian required by schools as consumers to operate the curriculum, and to suggest ways to improve their professionality. To this end, the duties and competencies included in 20 job advertisements posted by IB schools to select teacher librarians were analyzed based on the IFLA School Library Guidelines. As a result of the analysis, it was found that the duties and competencies of IB schools are based on the IB curriculum guidelines and this guideline is based on the educational philosophy and learner image that IBO curriculum aims. And the job that schools want the most from the teacher librarian is teaching through library collection management and collaboration, and the main competencies for this are communication and collaboration skills, teaching-learning·curriculum·education design and operation, and digital & media literacy. The results of this analysis show that the professionalism should be based on the vision for the educated person and learner capabilities presented in the curriculum. Based on this results, in this study the ways for developing teacher librarians' professionalism were presented in the following aspects. First, including the educational responsibilities of the school library in the Arrangement and Implementation Guideline of National Level Curriculum. Second, Classifying human resources' duties through revision of the Enforcement Decree of the School Library Promotion Act. Third, reorganizing of basic courses to acquire teacher librarian qualifications and introducing a demonstration of collaborative teaching in the eduactional practice and the certification examination.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.57-74
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• 2022

Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.