• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1869-1876
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• 2014

Car rear-view camera system supplies various services for life protection, ease of parking, and safe driving by showing the rear of the vehicle through monitor when reversing the car. In this paper we researched development methods and design of a Car Rear-view Camera System based on the Binary CDMA technology - new technology of wireless personal area network developed by Korea - that makes free installation without wired cables restriction and reduces installation costs and technology royalties.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.66-72
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• 2004

To assess tunnel safety, cracks in tunnel lining are measured by inspectors, who observe cracks with their naked eyes and record them. But manual inspection is slow, and measured crack data is subjective. Therefore, this study proposes inspection system fur measuring cracks in tunnel lining and providing objective crack data to be used in safety assessment. The system consists of On-vehicle system and Laboratory system. On-Vehicle system acquires image data with line CCD camera on scanning along the tunnel lining. Laboratory system extracts crack information from the acquired image using image processing. Measured crack information is crack thickness, length and orientation. To improve accuracy of crack recognition, the geometric properties and patterns of cracks in concrete structure were applied to image processing. The proposed system was verified with experiments in both laboratory environment and field environment such as subway tunnel.

• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.1-7
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• 2003

Autonomous underwater vehicles (AUVs) are unmanned, underwater vessels that are used to investigate sea environments in the study of oceanography. Docking systems are required to increase the capability of the AUVs, to recharge the batteries, and to transmit data in real time for specific underwater works, such as repented jobs at sea bed. This paper presents a visual :em control system used to dock an AUV into an underwater station. A camera mounted at the now center of the AUV is used to guide the AUV into dock. To create the visual servo control system, this paper derives an optical flow model of a camera, where the projected motions of the image plane are described with the rotational and translational velocities of the AUV. This paper combines the optical flow equation of the camera with the AUVs equation of motion, and deriver a state equation for the visual servo AUV. Further, this paper proposes a discrete-time MIMO controller, minimizing a cost function. The control inputs of the AUV are automatically generated with the projected target position on the CCD plane of the camera and with the AUVs motion. To demonstrate the effectiveness of the modeling and the control law of the visual servo AUV simulations on docking the AUV to a target station are performed with the 6-dof nonlinear equations of REMUS AUV and a CCD camera.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.290-293
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• 2013

Due to vehicle personal injury accident does not, and to analyze the cause and prevention of a variety of devices and technologies are coming out. Among other things, representative of the black box, and rear camera. Despite these advances in technology, and vehicle human injuries continue to occur. The reason for this is that the children, the negligence of the driver or the vehicle is in reverse when a person suddenly passed the back of the vehicle, or the rear of the existing detection system is properly detected was unable to. Therefore, In this paper, we want to design a black box to reveal the cause of the accident, using Kinect to prevent accidents, rear-view camera and rear integrated black box system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.303-308
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• 2011

Vehicle black boxes that have similar functions as airplane black boxes are currently being used due to the loss of many lives and properties arising from vehicle accidents. Both black-box products and Event Data Recorder(EDR) systems are currently available in the market. Most of the existing in-vehicle black boxes, however, record only external videos and images and cannot show the vehicle's driving status, whereas EDR products record only the driving status and not external videos. To address the problem of black boxes that can record only videos and images and that of EDR systems that can record only driving data, an integrated vehicle state and video recording system that uses MOST(Media-oriented System Transport) and OBD-II(Onboard Diagnostics II) and CAM (camera) and GPS (global positioning system).

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.