• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.147-153
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• 2015

We propose a detecting method for a car accident in parking lots. The proposed method consists of 3 parts : car detection, car tracking, and accident detection. In the car detection part, we detect the car using the pixel based foreground extraction method and the motion map. From the result of the car detection, the moving car is tracked. In the accident detection part, we set the accident detecting region in front of car, and then the car accident is detected using the difference of the motion. Experimental results show that the proposed method effectively detects the car accident in the parking lots.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.501-509
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• 2004

The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1285-1290
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• 2004

Crossing is the place which train, car and pedestrian adjoin, and the weak place. Also, crash accident between train and large size car is possible to be serious. So, various crossing obstacle detection device was developed, and it contribute to reduce the crossing accident.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.91-105
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• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2677-2685
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• 2013

Car running data collected from the vehicle is a native image data and sensing data of it. Hence, it can be used as a set of objective data based on which events that took place outside the car can be analyzed and determined. In this paper, we designed and implemented a emergency situation detection system to sense, store, and analyze signals related to car movements, driver's various operation states, collision pulse, etc when a car collision accident occurs on the actual road by sensing and analyzing the car movements and driver's operation status. The suggested system provides information on the driver's reaction right before the collision, operation state of the vehicle, and physical movement. The collected and analyzed data on vehicle running can be utilized to clarify the cause of a collision accident and to handle it in a just manner. Besides, it can contribute to grasping and correcting wrong driving habits of the driver and to saving.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.699-704
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• 2016

In this paper, we propose a development method for a drowsiness detection system using retinex theory and edge information for vehicle safety. Detection of a drowsy state of a driver is very important because the drowsiness of driver is often the main cause of many car accidents. After acquiring an image of the entire face, we executed the pre-process step using the retinex theory. We then applied a technique for the detection of the white pixels using edge information. Experimental results showed that the proposed method improved the accuracy of detecting drowsiness to nearly 98%, and can be used to prevent a car accident caused by the driver's drowsiness.

• Smart Media Journal
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• v.4 no.1
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• pp.39-43
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• 2015

A vehicle black box helps to investigate the cause of accident by recording time, and videos as wells as shock information of the time of accident Lately, intelligent black box with accident prevention as well as existing functions is being studied. This paper proposes an applicable algorithm for vehicle black boxes that prevent any accident likely to occur while a car is parked, like robbery, theft or hit-and-run. Proposed algorithm provides object recognition, face detection and alarm as the object approaches car. Tests on the algorithm prove that it can recognize an approaching object, identify and set alarm if needed, depending on each risk level.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.457-463
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• 2012

Changing the environment around detecting areas may lower the performance of a video-based accident detection system. Region of interest(ROI) and background information changing constantly on account of the car headlights at night and a sudden changes in the weather are the biggest factors to increase the ratio of wrong results. Thus, we proposed and implemented the integrated accident detection system combined the video-based system and the laser-based imaging system. In this paper, we were able to overcome the majority problem of video-based system and it was a meaningful results that it can improve the reliability for the system.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2942-2950
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• 2010

Car black box helps to investigate the cause of accident by recording time, position and videos as well as shock information. In addition, the car black box need a function to support safe driving for preventing accident. The representative driving support function is a lane departure warning. In order to implement the function, it is necessary to carry out the image processing to detect the lane first. The image processing algorithm requires computational burden to handle so much data and complicated structure of algorithm. This paper describes the efficient image processing algorithm with relatively low amount of computation for car black box embedded platform to detect lanes from the real-time lane image.