• Journal of the Korean Society of Safety
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• v.23 no.5
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• pp.7-14
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• 2008

The temperature distribution in a surface of diesel particulate filter(DPF) was measured using an infrared temperature camera. In order to regenerate the DPF, five partitioned electric heaters were used for heating the ceramic filter. The five partitioned heaters were switched on/off with some time interval one the other. The surface temperature distribution in the ceramic filter and electric heaters were measured with varying both the electrical power supply to the heaters and the mass flow rate of the air supply from a blower. The higher mass flow rate in the DPF system enhanced the uniformity in the surface temperature distribution of the ceramic filter due to effective convection heat transfer. The flow in the monolith ceramic structure of the DPF move mainly in the axial direction, which could be identified from the surface temperature of the ceramic filter.

• Annual Conference of KIPS
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• 2019.05a
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• pp.419-422
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• 2019

The recent increase in single-person households and family income has led to an increase in the number of pet owners. However, due to the owners' difficulty to communicate with them for 24 hours, pets, and especially dogs, tend to display unwanted behavior that can be harmful to themselves and their environment when left alone. Therefore, detecting those behaviors when the owner is absent is necessary to suppress them and prevent any damage. In this paper, we propose a camera-based system that detects a set of normal and unwanted behaviors using deep learning algorithms to monitor dogs when left alone at home. The frames collected from the camera are arranged into sequences of RGB frames and their corresponding optical flow sequences, and then features are extracted from each data flow using pre-trained VGG-16 models. The extracted features from each sequence are concatenated and input to a bi-directional LSTM network that classifies the dog action into one of the targeted classes. The experimental results show that our method achieves a good performance exceeding 0.9 in precision, recall and f-1 score.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.285-290
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• 2003

In this paper, a camera modeling method that utilizes ephemeris data and imaging geometry is presented. The proposed method constructs a mathematical model only with parameters that are contained in auxiliary files and does not require any ground control points for model construction. Control points are only needed to eliminate geolocation error of the model that is originated from errors embedded in the parameters that are used in model construction. By using a few (one or two) control points, RMS error of around pixel size can be obtained and control points are not necessarily uniformly distributed in line direction of the scene. This advantage is crucial in large-scale projects and will enable to reduce project cost dramatically.

• Korean Journal of Optics and Photonics
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• v.2 no.4
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• pp.179-185
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• 1991

Twyman-Green interferometer is developed for assessment of IR optical system performance. Light source is $CO_2$ gas laser which has 10.6$\mu \textrm m$ wavelength. The light beam is expanded to 2.5 cm dia by Ge lens and splitted by ZnSe parallel plane plate. One of the beams is reflected by refernce mirror which is operated PZT. The fringe will be detected by a pyro-electric vidicon camera and displayed by a CRT monitor. Here, the IR firinge is recorded on the thermal paper. In visible region, the light source is He-Ne laser. The fringe is detected by a CCD camera and displayed by the CRT monitor. The intensity of the fringe is digitized by a image card and processed by a PC. The wavefront aberration function, PSF and OTF are calculated. The results are displayed in 3-D graphs on the monitor or printed out by a line printer.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.229-239
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• 2022

Today's Internet of Things (IoT) has had a dramatic increase in the use of various daily aspects. As a consequence, many homes adopt IoT technology to move towards the smart home. So, the home can be called smart when it has a range of smart devices that are united into one network, such as cameras, sensors, etc. While IoT smart home devices bring numerous benefits to human life, there are many security concerns associated with these devices. These security concerns, such as user privacy, can result in an insecure application. In this research, we focused on analyzing the vulnerabilities of IoT smart home cameras. This will be done by designing a new model that follows the STRIDE approach to identify these threats in order to afford an efficient and secure IoT device. Then, apply a number of test cases on a smart home camera in order to verify the usage of the proposed model. Lastly, we present a scheme for mitigation techniques to prevent any vulnerabilities that might occur in IoT devices.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.72-78
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• 2023

The leopard (Panthera pardus) is one of the most widespread felids worldwide. Despite their wide distribution, reliable data on leopard population densities are still inadequate for conservation and management strategies in different landscapes. In the present study, we estimated leopard density using camera traps in the Ranthambhore Tiger Reserve (RTR), Rajasthan, India, between December 2010 and February 2011, where leopards coexist alongside a high density of tigers (Panthera tigris), a larger predator (RTR). A sampling effort of 4,450 trap days was made from 178 camera trapping stations over 75 days, resulting in 46 suitable photo captures (25 right flanks and 21 left flanks). In total, 18 individuals (7 males, 8 females, and 3 unknown sexes) were identified using the right flanks, and the estimated leopard density was 8.8 (standard error=2.8) individuals/100 km². Leopard density appeared to respond to small prey (<50 kg weight) richness. As this is the first systematic study to provide baseline information on leopard density in RTR, it could form a baseline for comparison in future investigations.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.117-121
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• 2020

Many of hotel customers obtain information from hotel websites to find the best alternative. One of the crucial information for the choice is spatial/visual information of hotel rooms. However, hotel website provides photographs only showing representative room features that may not be sufficient to give a full understanding of hotel room to customers. HMD-based 3D virtual environments (HVE) created by 3D camera could improve customers' experiences of hotel rooms by providing full virtual tours of hotel rooms. However, to the best of our knowledge, whether HVE can adequately provide similar customers' perception on spatial/visual information remains unproven as physical hotel rooms. The present study thus aims to verify how similar and reliable information on physical hotel room HVE provides to hotel customers in comparison with hotel website with 2D photograph and display-based 3D virtual environment. For this purpose, this study conducted a comparative experiment to investigate perception of three environments. As a result, the study found that HVE is more effective to provide spatial/visual information as similar as an actual hotel room. In addition, HVE increases customers' perceptions towards the reliability of information, the quality of hotel room and intention to book.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.5
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• pp.235-242
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• 2024

In the context of urban autonomous driving, where various types of traffic lights are encountered, traffic light recognition technology is of paramount importance. We have designed a high-performance traffic light recognition module tailored to scenarios encountered in domestic urban driving and devised a dataset construction process. In this paper, we focus on minimizing the camera's dependency to enhance traffic light recognition performance. The camera is used solely to distinguish the color information of traffic lights, while accurate location information of the traffic lights is obtained through localization and a map. Based on the information from these components, camera RoIs (Region of Interest) are extracted and transmitted to the embedded board. The transmitted images are then sent back to the main system for autonomous driving control. The processing time for one traffic light RoI averages 43.2 ms. We achieve processing times of average 93.4 ms through batch inference to meet real-time requirements. Additionally, we design a data construction process for collecting, refining, and storing traffic light datasets, including semi-annotation-based corrections.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.301-312
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• 2005

Three different cases should be considered for motion tracking: moving object with fixed camera, fixed object with moving camera and moving object with moving camera. Two methods are widely used for motion tracking: the optical flow method and the difference frame method. The optical new method is mainly used when either one, object or camera is fixed. This method tracks object using time-space vector which compares object position frame by frame. This method requires heavy computation, and is not suitable for real-time monitoring system such as DVR(Digital Video Recorder). The different frame method is used for moving object with fixed camera. This method tracks object by comparing the difference between background images. This method is good for real-time applications because computation is small. However, it is not applicable if the camera is moving. This thesis proposes and implements the motion tracking system using the difference frame method with PTZ(Pan-Tilt-Zoom) control. This system can be used for moving object with moving camera. Since the difference frame method is used, the system is suitable for real-time applications such as DVR.