• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.713-725
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• 2019

Automatic License Plate Recognition (ALPR) is a technology required for many applications such as Intelligent Transportation Systems and Video Surveillance Systems. Most of the studies have studied were about the detection and recognition of license plates on cars, and there is very little about detecting and recognizing license plates on motorbikes. In the case of a car, the license plate is located at the front or rear center of the vehicle and is a straight or slightly sloped license plate. Also, the background of the license plate is mainly monochromatic, and license plate detection and recognition process is less complicated. However since the motorbike is parked by using a kickstand, it is inclined at various angles when parked, so the process of recognizing characters on the motorbike license plate is more complicated. In this paper, we have developed a 2-stage YOLOv2 algorithm to detect the area of a license plate after detection of a motorbike area in order to improve the recognition accuracy of license plate for motorbike data set parked at various angles. In order to increase the detection rate, the size and number of the anchor boxes were adjusted according to the characteristics of the motorbike and license plate. Image warping algorithms were applied after detecting tilted license plates. As a result of simulating the license plate character recognition process, the proposed method had the recognition rate of license plate of 80.23% compared to the recognition rate of the conventional method(YOLOv2 without image warping) of 47.74%. Therefore, the proposed method can increase the recognition of tilted motorbike license plate character by using the adjustment of anchor boxes and the image warping which fit the motorbike license plate.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.556-559
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• 2007

고탁수 장기화 문제를 해결하기 위한 방법으로는 고탁수층을 선택취수하여 우선 배제함으로써 하류하천의 고탁수 발생일수를 최소화하는 방법이 있는데, 이와 같은 선택적 취수기법은 저수지 운영에 있어서 고탁수층을 우선 배제한 후 홍수기 이후에 저수지내로 유입되는 청수를 담수하여 호소 내 탁도 저감 효과를 얻을 수 있다. 본 연구에서는 선택취수 시 성층수괴의 동수역학적 변화를 분석하기 위하여 국내에서 처음으로 Two-tank 기법을 이용하여 성층구조를 구현해 내었는데, 소금물의 밀도변화를 이용하여 수심 1m의 성층수조를 만들었고, 밀도경사가 상이한 성층구조에서 취수조건을 변화시키면서 비교란 유속계인 PIV 시스템을 이용해 유속의 흐름을 Vector와 Contour로 분석하였다. 선택취수에 대한 흐름의 동수역학적 분석결과 취수유량보다는 밀도성층경사 변화에 더 민감한 반응을 보였다. 취수유량을 줄이거나 밀도성층경사를 급하게 했을 때에는 선택취수 영역(withdrawal zone)의 수직방향 폭은 줄어드는 반면, X축으로의 영향범위는 증가함을 나타냈다. 취수유량을 증가시키거나 성층밀도경사를 완만히 했을 땐 선택취수 영역(withdrawal zone)의 수직방향 폭은 증가하였고 X축으로의 영향범위는 축소됨을 나타내었다. 이 결과는 Richardson 수로도 판단되어지는데, Richardson 수가 증가하면 유속에 비해 상대적으로 밀도성층경사가 크다는 것인데 이럴 경우 선택취수 영역(withdrawal zone)의 수직방향 폭 최대가 되고 선택취수 영역(withdrawal zone)의 수직방향 폭은 최소가 된다. 선택취수 영역(withdrawal zone)의 수직방향 폭이 최소가 되면 취수구 직경 D의 1.8배의 값을 가지고 Richradson 수가 최소가 되더라도 취수구 직경 D의 3.3배를 벗어나지 않는다는 결과를 도출할 수 있었다.링 목적으로 사용될 수 있다. 본 연구에서 개발한 영상수위계는 한강홍수통제소 관할의 전류, 청담대교 등 4개소 낙동강 홍수통제소 2개소, 지자체 등에 적용되었으며, 적용 결과 비교적 안정적이면서 정확하게 수위를 측정하는 것으로 나타났다. 한편 기존 CCD 카메라 이외에 CCTV를 이용한 영상수위계를 개발하여 영상의 화질 개선뿐 아니라 하천화상 감시 기능을 강화하였다.소류의 섭취율은 높았다. 집단간의 상관도를 보면 교육별로 김치, 장아찌, 콩이 각각 p>0.5 수준에서 유의한 차가 없었고, 나머지는 유의한 차가 있었다. 연령별로는 멸치가 유의한 차가 없었고(p>0.5), 수입별로는 콩이 유의한 차가 없었다(p>0.5). 4. 영양지식(營養知識) 검토 가정생활(家庭生活)에 필요(必要)한 일반적(一般的)인 영양지식(營養知識)은 대체적으로 낮은 편이었다. 어린이 영양, 편식의 해로움, 비만증의 해로움, 임신부 그리고 수유부 영양에 대하여는 일반적으로 알고 있다고 하였으며, 그다음으로 이유기 영양, 어린이 발육에 필요한 식품, 식품과 영양소와의 관계, 우유의 성분, 노인영양에 대하여 잘 알고 있는 비율이 낮았으며, 인체의 영양소, 식단작성여부, 간식의 이론, 식품감별법에 대하여는 가장 낮은 비율을 나타냈다. 각 영양지식은 교육정도가 높을수록 영양지식이 높았고, 교육별 집단간의 유의한 차가 나타났다. (0.001

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1173-1183
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• 2023

Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.1-8
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• 2020

If a dangerous situation arises in a place where out of reach from the human, UAVs can be used to determine the size and location of the situation to reduce the further damage. With this in mind, this paper sets the minimum value of the roll, pitch, and yaw using beta flight to detect the UAV's smooth hovering, integration, and derivative (PID) values to ensure that the UAV stays horizontal, minimizing errors for safe hovering, and the camera uses Open CV to install the Raspberry Pi program and then HSV (color, saturation, Brightness) using the color palette, the filter is black and white except for the red color, which is the closest to the fire we want, so that the UAV detects the image in the air in real time. Finally, it was confirmed that hovering was possible at a height of 0.5 to 5m, and red color recognition was possible at a distance of 5cm and at a distance of 5m.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.296-303
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• 2014

In this paper, we propose an algorithm to visualize radio wave environment based on the measured Received Signal Strength Indication( RSSI) and 3D geographic information. We estimate the source position using the circumcenter of the triangle and visualize the radio wave environment using the empirical propagation models. A mode seeking algorithm(mean-shift clustering) is used to seek the peak points and the center of gravity is utilized to reduce the estimation errors. Our approach finds its applications in the radio wave monitoring systems for the efficient utilization of radio resources.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.93-98
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• 2011

In this paper, we propose the surveillance and combat robot framework for remote monitoring and robot control on the smart phone, which is implemented with the fusion technology called RITS(Robot technology & Information Technology System). In our implemented system, the camera phone mounted on the robot generates signals to control the robot and sends images to the smart phone of the operator. Therefore, we can monitor the surrounding area of the robot with the smart phone. Besides the control of the movement of the robot, we can fire the weapons armed on the robot by sending the fire command. From experimental results, we can conclude that it's possible to control the robot and monitor the surrounding area of the robot and fire the weapons in real time in the region where the 3G(Generation) mobile communication is possible. In addition, we controlled the robot using the 2G mobile communication or wired phone when the robot is in the visual range.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.80-87
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• 2011

In this paper we present subject region-based auto-focusing algorithm using noise robust focus measure. The proposed algorithm automatically estimates the main subject using entropy and solves the traditional problems with a subject position or high frequency component of background image. We also propose a new focus measure by analyzing the discrete cosine transform coefficients. Experimental results show that the proposed method is more robust to Gaussian and impulse noises than the traditional methods. The proposed algorithm can be applied to Pan-tilt-zoom (PTZ) cameras in the intelligent video surveillance system.