• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.818-828
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• 2014

After emerging of Microsoft Kinect, the interest in three-dimensional (3D) depth image was significantly increased. Depth image data of an object can be converted to 3D coordinates by simple arithmetic calculation and then can be reconstructed as a 3D model on computer. However, because the surface coordinates can be acquired only from the front area facing Kinect, total solid which has a closed surface cannot be reconstructed. In this paper, 3D registration method for multiple Kinects was suggested, in which surface information from each Kinect was simultaneously collected and registered in real time to build 3D total solid. To unify relative coordinate system used by each Kinect, 3D perspective transform was adopted. Also, to detect control points which are necessary to generate transformation matrix, 3D randomized Hough transform was used. Once transform matrices were generated, real time 3D reconstruction of various objects was possible. To verify the usefulness of suggested method, human arms were 3D reconstructed and the volumes of them were measured by using four Kinects. This volume measuring system was developed to monitor the level of lymphedema of patients after cancer treatment and the measurement difference with medical CT was lower than 5%, expected CT reconstruction error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.13-22
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• 2007

In this paper, we propose an audience counting method in an auditorium based on pattern comparison. The previous counting methods based on object detection can't exactly count the audience in real time because auditorium has coarse illumination condition and so many audiences. Therefore, in this paper, we count the audience in an auditorium with fixed seats by the method which the pattern from each reference seat is compared to the pattern from each input seat. Especially, to overcome limitations based on either illumination or noise, two pattern comparison methods are efficiently employed and combined. One is based on the amplitude projection, and the other is based on Walsh-Hadamard Kernel. Walsh-Hadamard Kernel has the characteristic which complements amplitude projection. Therefore, we ran achieve the accurate counting in the presence of coarse illumination and noise. The experimental results show that our method performs well on sequences of images acquired in an auditorium. We also verify a realistic possibility for other applications applying our method to the parking positioning system.

• Proceedings of the KSRS Conference
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• v.1
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• pp.106-109
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• 2006

Over the years, many researches have been performed to create 3D digital maps. Nevertheless, it is still time-consuming and involves a high cost because a large part of 3D digital mapping is conducted manually. To compensate this limitation, we propose methodologies to represent 3D objects as 3D symbols and locate these symbols into a base map automatically. First of all, we constructed the 3D symbol library to represent 3D objects as 3D symbols. In the 3D symbol library, the attribute and geometry information are stored, which defines factors related to the types of symbols and related to the shapes respectively. These factors were used to match 3D objects and 3D symbols. For automatic mapping of 3D symbols into a base map, we used predefined parameters such as the size, the height, the rotation angle and the center of gravity of 3D objects which are extracted from Light Detection and Ranging (LIDAR) data and 2D digital maps. Finally, the 3D map in urban area was constructed and the mapping results were tested using aerial photos as reference data. Through this research, we can identify that the developed the algorithms can be used as effective techniques for 3D digital cartographic techniques

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.89-96
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• 2017

This Paper proposes a vehicle detection system and a license plate recognition system from CCTV images installed on public roads. Since the environment of this system acquires the image in the general road environment, the stable condition applied to the existing vehicle entry / exit system is not given, and the input image is distorted and the resolution is irregular. At the same time, the viewing angle of the input image is more wide, so that the computation load is high and the recognition accuracy of the plate is likely to be lowered. In this paper, we propose an improved method to detect and recognize a license plate without a separate input control devices. The vehicle and license plate were detected based on the HOG feature descriptor, and the characters inside the license plate were recognized using the k-NN algorithm. Experimental environment was set up for the roads more than 45m away from the CCTV, Experiments were carried out on an entry vehicle capable of visually identifying license plate and Experimental results show good results of the proposed method.

• Journal of Forest and Environmental Science
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• v.30 no.2
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• pp.233-242
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• 2014

Estimating above-ground biomass is important in establishing an applicable methodology of Measurement, Reporting and Verification (MRV) System for Reducing Emissions from Deforestation and Forest Degradation-Plus (REDD+). We developed an estimation model of diameter at breast height (DBH) from IKONOS-2 image that led to above-ground biomass estimation (AGB). The IKONOS image was preprocessed with dark object subtraction and topographic effect correction prior to watershed segmentation for tree crown delineation. Compared to the field observation, the overall segmentation accuracy was 64%. Crown detection percent had a strong negative correlation to tree density. In addition, satellite-based crown area had the highest correlation with the field measured DBH. We then developed the DBH allometric model that explained 74% of the data variance. In average, the estimated DBH was very similar to the measured DBH as well as for AGB. Overall, this method can potentially be applied to estimate AGB over a relatively large and remote tropical forest in Northern Borneo.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.563-572
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• 2020

Tidal flats provide important indicators that inform the condition of the environment, so we need to monitor them systematically. Currently, the projects to monitor tidal flats by periodically observing the creatures in tidal flats are underway. Still, it is done in a way that people observe directly, so it is not systematic and efficient. In this paper, we propose a background modeling method for tidal flat images that can be applied to a system that automatically monitors creatures living in tidal flats using sensor network technology. The application of sensor network technology makes it difficult to collect enough images due to the limitation of transmission capacity. Therefore, in this paper, we propose a method to effectively model the background and generate foreground maps by reflecting the characteristics of tidal flat images in the situation where the number of images to be used for analysis is small. Experimental results show that the proposed method models the background of a tidal flat image easily and accurately.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.159-164
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• 2015

Color is distinguished due to the light in which natural light is reflected by object and made with combination of RGB(red, green, blue; three colors). This study proposes color analysis system with optical method to be used conveniently. Color information of sample is determined with the optical sensor. By using the CIE diagram in particular, it detects purity value and wavelength. The method to distinguish color is very economical, simple, and convenient. The result can be used to confirm accurate information of color for various applications.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.67-73
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• 2010

We have developed a millimeter-wave passive imaging system with reflector for detection of concealed objects. We have designed a millimeter-wave sensor, control device for reflector control, and a lens for focusing of millimeter-wave signal at center frequency of 94GHz. DC signal from millimeter-wave sensor output is filtered by low pass filter and amplified by video amplifier, and then converted into digital signal by using ADC/DAQ. This signal is image processed by computer, and it is possible to obtain millimeter-wave passive image with resolution of $18{\times}64$ pixel using the fabricated system. It is shown that we can obtain the image of men and concealed object with the system.