• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1649-1656
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• 2016

Performance of the existing sensor-based fire detection system is limited according to factors in the environment surrounding the sensor. A number of image-based fire detection systems were introduced in order to solve these problem. But such a system can generate a false alarm for objects similar in appearance to fire due to algorithm that directly defines the characteristics of a flame. Also fir detection systems using movement between video flames cannot operate correctly as intended in an environment in which the network is unstable. In this paper, we propose an image-based fire detection method using CNN (Convolutional Neural Network). In this method, firstly we extract fire candidate region using color information from video frame input and then detect fire using trained CNN. Also, we show that the performance is significantly improved compared to the detection rate and missing rate found in previous studies.

• Convergence Security Journal
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• v.11 no.4
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• pp.59-66
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• 2011

Recently, it is very important to establish and predict a traffic policy for expanding social infra structure like road, because the number of cars is significantly increasing. In this paper, we propose and develop an automated system technology based on vision sensor (CCTV) which can provide an efficient information for the traffic policy establishment and expanding the social infra structure. First, the CCTV image is captured as an input of the developed system. With this image, we propose a scheme for extracting vehicles on the road and classifying small-type, large-type vehicles based on color, motion, and geometric features. Also, we develop a DB (database) system for supplying a whole information of traffic for a specified period. Based on the proposed system, we verify 90.1% of recognition ratio in real-time traffic monitering environment.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.23-30
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• 2010

It is important for the strategy of cosmetic sales to investigate the sensibility and the preference degree in the environment that the makeup style has been changed focusing on the consumer center. We proposed the human sensibility ergonomics makeup recommendation system (MakeupRS) using the context sensor information applying the collaborative filtering technique as one of methods in the makeup style development centered on the consumer's sensibility and the preference. In the collaborative filtering technique, the Pearson correlation coefficient applying to the case amplification is used to calculate similarity weights between the users. To investigate the sensibility according to the effect of makeup styles, the makeup styles were analyzed in terms of 6 style factors, such as, the foundation, the color lens, the eye shadow, the eye lash, the cheek brusher, and the lipstick. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the human sensibility ergonomics makeup recommendation system.

• Proceedings of KOSOMES biannual meeting
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• 2003.11a
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• pp.191-193
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• 2003

Temporal and spatial variability of phytoplankton pigment concentrations around the Korea Peninsula was described, using the monthly mean composite images of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor). The high pigment concentrations appear in the spring and fall in the East Sea The spring bloom in the southern regions (in April) occurs one month in advance in comparison with tint in the northern regions (in May). In summer season, the pigment concentrations are low all over the region in the East Sea And the high pigment concentrations exist yearly around warm stream along the coast of the East Sea, and in the coast of the West Sea and South Sea In particular, the high pigment concentrations linking near the mouth q the Yangze River to coast of South Sea in Korea appear during August to December.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.68-73
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• 2005

Various techniques have been proposed for detection and tracking of targets in order to develop a real-world computer vision system, e.g., visual surveillance systems, intelligent transport systems (ITSs), and so forth. Especially, the idea of distributed vision system is required to realize these techniques in a wide-spread area. In this paper, we develop a ubiquitous vision system for location-awareness of multiple targets. Here, each vision sensor that the system is composed of can perform exact segmentation for a target by color and motion information, and visual tracking for multiple targets in real-time. We construct the ubiquitous vision system as the multiagent system by regarding each vision sensor as the agent (the vision agent). Therefore, we solve matching problem for the identity of a target as handover by protocol-based approach. We propose the identified contract net (ICN) protocol for the approach. The ICN protocol not only is independent of the number of vision agents but also doesn't need calibration between vision agents. Therefore, the ICN protocol raises speed, scalability, and modularity of the system. We adapt the ICN protocol in our ubiquitous vision system that we construct in order to make an experiment. Our ubiquitous vision system shows us reliable results and the ICN protocol is successfully operated through several experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.597-602
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• 2014

We propose hybrid-sensing system for human tracking. This system uses laser scanners and image sensors and is applicable to wide and crowded area such as hallway of university. Concretely, human tracking using laser scanners is at base and image sensors are used for human identification when laser scanners lose persons by occlusion, entering room or going up stairs. We developed the method of human identification for this system. Our method is following: 1. Best-shot images (human images which show human feature clearly) are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the color histograms of best-shot images. It becomes possible to conduct human identification even in crowded scenes by estimating best-shot images. In the experiment in the station, some effectiveness of this method became clear.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.218.2-218.2
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• 2012

In the remote sensing researches, the reflected bright source such as snow, cloud have effects on the image quality of wanted signal. Even though those signal from bright source are adjusted in corresponding pixel level with atmospheric correction algorithm or radiometric correction, those can be problem to the nearby signal as one of the stray light source. Especially, in the step and stare observational method which makes one mosaic image with several snap shots, one of target area can affect next to the other snap shot each other. Presented in this paper focused on the stray light analysis from unwanted reflected bright source for geostationary ocean color sensor. The stray light effect for total 16 slot images each other were performed according to 8 band filters. For the realistic simulation, we constructed system modeling with integrated ray tracing technique which realizes the same space time in the remote sensing observation among the Sun, the Earth, and the satellite. Computed stray light effect in the results of paper demonstrates the distinguishable radiance value at the specific time and space.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.69-73
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• 2014

Recent interest in the worldwide energy to increase, and energy savings of the energy for effective operation of the IT technology there is a demand. By using a low-power LED energy efficient energy use worldwide for a variety of studies have been conducted. In Korea, 20-30% of the domestic electricity consumption corresponding to the illumination in order to conserve energy used by various sensors associated with illumination control studies are underway. That is the next generation of energy began to pay attention to the LED light source, LED and Arduino In this paper, an ultrasonic sensor to control and want to maximize the energy efficiency of the management. Paper, the user is directly operating the separate controller that controls the LED light, instead of being recognized through human body detection LED light on / off to control the experiment and study verified. In this paper, we develop an interface that also allows them to maximize the efficiency of energy management and efficiency, accompanied by expansion of commercialization can be achieved.

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.357-365
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• 1999

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the KOrea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in late 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As a part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed, archived, and provided. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

• Smart Media Journal
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• v.11 no.9
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• pp.56-63
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• 2022

Recently, the frequency and range of algae occurrence in major rivers and lakes are increasing due to the increase in water temperature due to climate change, the inflow of excessive nutrients, and changes in the river environment. Abnormal algae include green algae and red algae. Green algae is a phenomenon in which blue-green algae such as chlorophyll (Chl-a) in the water grow excessively and the color of the water changes to dark green. In this study, a 3D virtual world of digital twin was built to monitor and control water quality information measured in ecological rivers and lakes in the living environment in real time from a remote location, and a sensor measuring device for water quality information based on the Internet of Things (IOT) sensor. We propose to build a smart water environment service platform that can provide algae warning and water quality forecasting by predicting the causes and spread patterns of water pollution such as algae based on AI machine learning-based collected data analysis.