• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.693-698
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• 2018

This paper proposes a vehicle detection method for parking areas using unmanned aerial vehicles (UAVs) and using YOLOv2, which is a recent, known, fast, object-detection real-time algorithm. The YOLOv2 convolutional network algorithm can calculate the probability of each class in an entire image with a one-pass evaluation, and can also predict the location of bounding boxes. It has the advantage of very fast, easy, and optimized-at-detection performance, because the object detection process has a single network. The sliding windows methods and region-based convolutional neural network series detection algorithms use a lot of region proposals and take too much calculation time for each class. So these algorithms have a disadvantage in real-time applications. This research uses the YOLOv2 algorithm to overcome the disadvantage that previous algorithms have in real-time processing problems. Using Darknet, OpenCV, and the Compute Unified Device Architecture as open sources for object detection. a deep learning server is used for the learning and detecting process with each car. In the experiment results, the algorithm could detect cars in a dense area using UAVs, and reduced overhead for object detection. It could be applied in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.595-603
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• 2015

With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.

• Journal of Distribution Science
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• v.17 no.6
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• pp.85-90
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• 2019

Purpose - In China, electric vehicle industry has been increased attention as a environmental friendly transportation to solve pollution problems, and still growing to solve a technological gap issues in automobile industry. Although the interest of electric vehicle is getting bigger, there are not many studies that showing consumers' intention to purchase an electric vehicle. Because of this phenomenon, this study tried to find the factors which can affect the purchase intention of electric vehicle. Research design, data, and methodology - Drawing on the Planned Behavior Theory(TPB), this study examined attitude toward the behavior, subjective norm of environmental protection, and the influence of economic benefits on purchase intention through survey. we measure 233 Chinese samples. Results - The results showed that attitude toward electric vehicles, subjective norms of environmental protection, and economic benefits had a significant effect on purchase intention. To be specific, the consciousness of environmental protection, economic considerations, product image and its characteristic are all considerable aspects from the standpoint of Chinese consumers. In addition, we found that the higher the age group, the weaker relationship between attitude toward electric vehicle and purchase intention. Conclusion - This study suggests that diverse factors related to the purchase intention of electric car in China market and Chinese consumers. Especially, economic benefit factors, which have a statistically significant and significant influence on the purchase intention of electric vehicles, are not significant variables in the existing electric vehicle research. This result is considered to be the result of the fact that the electric vehicle is not only an automobile having an environmentally friendly factor but also a product which makes it consider the economic situation. Put together, the results of this paper give us the theoretical basis for establishing an electric vehicle marketing strategy in the rapidly changing Chinese market. Also, this paper will provide new ventures for marketing and distribution strategies for Korean companies that are looking to expand into China.

• The Journal of the Korea Contents Association
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• v.6 no.8
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• pp.57-67
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• 2006

The motion effect of animation can be maximized by using the intended number of frame(flickering phenomena) responding to the viewer's perception in the production processes. But, the high contrast of chroma in a color arrangement can cause very dangerous situation if a particular effect(scheduled number of frame for the intended rapid flickering in a zoom-in scene of the warning light of police car and the traffic light) or a excessive visual stimulus is tried. The danger of flickering phenomena is defined as 'Flash Nervousness Attack Symptom' in medical terminology, which has received wide attention because the damage to the viewers of Pocket Monster was very serious in Japan. Producing a piece of animation work, the quality control of colors is important but the color setting considering the psychological aspects, the danger of repetitive flickering of flashes and patterns in image effect are more serious, so these factors should be checked in the production stages. After investigating the domestic and foreign prescriptions including the guidelines for animation production technique in Japan, a solution to reduce the danger of flickering phenomena of color and light was suggested through statistical comparative analysis with the test results.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.341-347
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• 2015

This study aims to design a chief VDR(Voyage Data Recorder) system which is appropriate to small and medium sized vessels and also implement the data about marine communication devices, sensors, etc. to be stored or printed at the navigator when those data are connected to VDR through data communication between marine navigation and VDR which are based on serial communication or internet in order to prove efficiency of the marine navigator. Also, the design of VDR is intended to be small and light in order to expand to apply it to small and medium vessels, which enables to analyze causes of marine accidents precisely through its characteristic functions which are the same as those at "vehicle mounted black-box" (location of the car, image and voice storage) by which the same roles are played on land.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.175-182
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• 2010

The paper presents a novel algorithm for face and iris detection with the application for driver iris monitoring. The proposed algorithm consists of the following major steps: Skin-color segmentation, facial features segmentation, and iris positioning. For the skin-segmentation we applied a multi-layer perceptron to approximate the statistical probability of certain skin-colors, and filter out those with low probabilities. The next step segments the face region into the following categories: eye, mouth, eye brow, and remaining facial regions. For this purpose we propose a novel segmentation technique based on estimation of facial class probability density functions (PDF). Each facial class PDF is estimated on the basis of salient features extracted from a corresponding facial image region. Then pixels are classified according to the highest probability selected from four estimated PDFs. The final step applies the circular Hough transform to the detected eye regions to extract the position and radius of the iris. We tested our system on two data sets. The first one is obtained from the Web and contains faces under different illuminations. The second dataset was collected by us. It contains images obtained from video sequences recorded by a CCD camera while a driver was driving a car. The experimental results are presented, showing high detection rates.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.1-12
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• 2003

DAB(Digital audio broadcasting) is a next generation radio broadcasting system which provides CD quality audio, various data services and superior reception ability when moving. Also, it can show traffic informations and news literally or graphically. In this paper, we design and fabricate the DAB tuner for ITS service that follows Eureka-147 and ETSI 300 401 specifications. This small-sized tuner can be adopted to mny electronic equipments such as a Hi-Fi audio, DVD player, car audio system etc.. The overall performance of the tuner depends on a phase noise of VCO and the sensitivity of the receiving system is influenced by LNA, image rejection filter and channel selection filter. All our measurement results satisfy the specification for a DAB system with the return loss of 9dB, the noise figure of 6dB for both Band 111 and L-band and the sensitivity of -97dBm.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.40-45
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• 2001

In this paper, we implemented a multimodal system combining speech and lip information, and evaluated its performance. We designed speech recognizer using speech information and lip recognizer using image information. Both recognizers were based on HMM recognition engine. As a combining method we adopted the late integration method in which weighting ratio for speech and lip is 8:2. By the way, Our constructed multi-modal recognition system was ported on DARC system. That is, our system was used to control Comdio of DARC. The interrace between DARC and our system was done with TCP/IP socked. The experimental results of controlling Comdio showed that lip recognition can be used for an auxiliary means of speech recognizer by improving the rate of the recognition. Also, we expect that multi-model system will be successfully applied to o traffic information system and CNS (Car Navigation System).