• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1287-1292
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• 2005

This paper presents an effective pattern classification model by designing an artificial neural network based pattern classifiers for face recognition. First, a RGB image inputted from a frame grabber is converted into a HSV image which is similar to the human beings' vision system. Then, the coarse facial region is extracted using the hue(H) and saturation(S) components except intensity(V) component which is sensitive to the environmental illumination. Next, the fine facial region extraction process is performed by matching with the edge and gray based templates. To make a light-invariant and qualified facial image, histogram equalization and intensity compensation processing using illumination plane are performed. The finally extracted and enhanced facial images are used for training the pattern classification models. The proposed H-ART2 model which has the hierarchical ART2 layers and F-LVQ model which is optimized by fuzzy membership make it possible to classify facial patterns by optimizing relations of clusters and searching clustered reference patterns effectively. Experimental results show that the proposed face recognition system is as good as the SVM model which is famous for face recognition field in recognition rate and even better in classification speed. Moreover high recognition rate could be acquired by combining the proposed neural classification models.

• Information and Communications Magazine
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• v.34 no.2
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• pp.12-19
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• 2017

The LED technology advancement introduce cuttingedge technology on Internet of Things (IoT) to connect the physical world to the digital realm, using digital smart lighting infrastructure called Internet of light (IoL). This paper proposes an Integrated IoT agent on networked smart LED lighting controller called IoL Filed Gateway using lighting infrastructure in which a lighting system that can connect to a network and can be monitored and controlled from a centralized system or via the cloud. The IoL Field Gateway defines new world of smart connected intelligence, lighting can become an integral and responsive part of everyday human life environments. The proposed connected lighting gateway uses the concept of multi-hop ad hoc network using visible light communication (VLC) with RF wireless technologies and Wired PLC (Power Line Communication). This connectivity and intelligence integrated into LED-based luminaires form the backbone of smart buildings and cities and make the Internet of Things (IoT) vision feasible and enables the lighting administrator can control numerous lightings easily and visitors can get visual information from the lightings with their smart devices. The proposed IoL gateway design is emulated on Arduino based HW platform with VLC, RF, and PLC connectivity and evaluated with four sensor interface.

• Journal of Technologic Dentistry
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• v.27 no.1
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• pp.57-63
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• 2005

Experimental Ti-13%Zr and Ti-13%Zr-5%Cu alloys were made in an argon-arc melting furnace. The grade 2 CP Ti was used to control. To investigate the surface reaction layers produced by the reaction with mold materials and the influence of the reaction layers on the hardness of castings, A phosphate bonded $SiO_2$ base investment was used as mold material, and microstructure observation and hardness test were performed. The surface reaction layers of Ti-13%Zr and Ti-13%Zr-5%Cu alloys were thinner than that of CP Ti had a clearly multiple structure. A difference of the hardness between surface and inner of the Ti-13%Zr and Ti-13%Zr-5%Cu alloys became less than that of CP Ti. From the results, it was found that the Ti-Zr-(Cu) based alloys were possible to cast with $SiO_2$ base investment without the great changes of mechanical properties of the castings.

• Journal of Technologic Dentistry
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• v.27 no.1
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• pp.65-71
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• 2005

Experimental Ti-13%Zr and Ti-13%Zr-5%Cu alloys were made in an argon-arc melting furnace. The grade 2 CP Ti was used to control. The alloys were cast into phosphate bonded $SiO_2$ investment molds using an argon-arc casting machine, and The hardness and microstructures of the castings were investigated in order to reveal their possible use for new dental casting materials and to collect useful data for alloy design. The hardness of the Ti-13%Zr-5%Cu alloy(379Hv) became higher than that of Ti-13%Zr(317Hv) alloy, and the hardness of this alloys became higher than that of CP Ti(247Hv). Increasing in the hardness of the Ti-13%Zr-5%Cu alloy was considered to be solid solution hardening as the Ti-Zr system shows a completely solid solution for both high temperature $\beta$phase and low temperature $\alpha$ phase and also the inclusion of the eutectoid structure($\alpha Ti+Ti_{2}Cu$). No martensitic structures are observed in the specimen made of CP Ti, but Ti-13%Zr and Ti-13%Zr-5%Cu alloys show a kind of martensitic structure. Ti-13%Zr-5%Cu shows the finest microstructure. From these results, it was concluded that new alloys for dental casting materials should be designed as Ti-Zr-Cu based alloys.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.107-129
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• 1996

Recently, surveillance system designed to collect various trsffic information are becoming new areas of development . Among these, the image detector is a ayatem which can measure the travel time and speed in realtime and this is emerging as the most effcient tool to be available in future related areas. But in measuring wide-area information in realtime, the image detector are yet full of problem in its accuracy. The aim of this ahesis is to develop an algorithms which can collect wide-area information such as travel time and travel speed in urban networks and freeways in realtime. The information on wide-area such as travel time and travel speed is important in accomplishing strategic function in traffic control. The algorithm developed from this study is based on the image tracking model which tracks a moving vehicle form image datas collected continuously, and is constructed to perform realtime measurement. To evaluate the performance of the developed algorithms, 600 ind vidual vehicles in total were used as data for the study, and this evaluation was carried out with the differenciation of day and night condition at the access roads in front of AJou University, In the statistical analysis results, the error rate was recorded as 5.69% and it has proved to be applicable on the field in both day and noght conditions.

• Journal of Biomedical Engineering Research
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• v.35 no.2
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• pp.14-18
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• 2014

This study is about e-Book program based on human-computer interaction(HCI) system for physically handicapped person. By acquiring background knowledge of HCI, we know that if we use vision-based interface we can replace current computer input devices by extracting any characteristic point and tracing it. We decided betweeneyes as a characteristic point by analyzing facial input image using webcam. But because of three-dimensional structure of glasses, the person who is wearing glasses wasn't suitable for tracing between-eyes. So we changed characteristic point to the bridge of the nose after detecting between-eyes. By using this technique, we could trace rotation of head in real-time regardless of glasses. To test this program's usefulness, we conducted an experiment to analyze the test result on actual application. Consequently, we got 96.5% rate of success for controlling e-Book under proper condition by analyzing the test result of 20 subjects.

• Current Optics and Photonics
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• v.3 no.2
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• pp.177-180
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• 2019

Based on liquid-lens technology and our previous findings on the optical model of the Chinese eye, the liquid lens is applied in the research of the crystalline-lens optical model. Theoretical models of three-layer liquid lenses are built with COMSOL software, and the effect of voltage on the shape of the interface between two liquids is analyzed. By polynomial fitting, different equations describing the interface shape are set up under different voltages. Finally, the optical system of the human eye with a three-layer liquid lens is built and analyzed with Zemax optical design software, and moreover the optical system models of emmetropia, myopia, and hyperopia are presented. This method to build a model of the human eye with a variable-focus liquid lens can provide a novel idea for more practical human-eye models for clinical regulation and control in the future.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.125-135
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• 2019

In recent years, the digital transformation age represented by the "Fourth Industrial Revolution", which is a universalization of digitalization across all industries, has become a reality. In the construction sector in 2018, the Ministry of Land, Infrastructure and Transport established the Smart Construction 2025 vision and established the 'Smart Construction Technology Roadmap' aiming to complete construction automation by 2030. Especially, in the construction stage, field monitoring technology using drones is needed to support construction equipment automation and on-site control, and a 3D geospatial information model can be utilized as a base tool for this. The purpose of this study is to investigate the factors affecting earthworks work in order to manage changes in site conditions and improve communication between managers and workers in the earthworks plan, which has a considerable part in terms of construction time and cost as a single type of work. Based on this, field management procedures and applications were developed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.426-432
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• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.