• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.1036-1040
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• 2002

To process data of digital linescan camera, the frame grabber is essential to handle the data in low-level and in high speed more than 30 MHz stably. Traditional approaches to the development of hardware in vision system for the special purpose are mai y based on PC system, and are expensive and gigantic. Therefore, there are many difficulties in applying those in the field. So we investigate, in this paper, the implementation of FPGA for real-time processing of digital linescan camera. The system is not based on PC, but electronic device such as micropncessor. So it is expected that the use of FPGAs for low-level processing represents a fast, stable and inexpensive system. The experiments are carried out on the web guiding system in order to show the efficiency of the new image processor.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.592-594
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• 2004

Camera calibration is an important problem to determine the relationship between 3D real world and 2D camera image. The existing calibration methods can be classified into linear and non-linear models. The linear methods are simple and robust against noise, but the accuracy expectation is generally poor. In comparison, if the non-linearity, which is due mainly to lens distortion, is corrected, the accuracy can be better. However, as the optical features of lens are diverse, no non-linear method can be always effective for diverse vision systems. In this paper, we propose a new approach to correct the calibration error of a linear method using GMDH algorithm. The proposed technique is simple in concept and showed improved accuracy in various cases.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.585-589
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• 2004

This paper deals with the algorithm development that inspects defects such as Lens Focus, Black Defect, Dim Defect, Color Defect, White Balance, and Line Defect caused by the process of Compact Camera Module (CCM). These days the demand of CCM goes on increasing in various types like PDA, a cellular phone and PC camera every year. However, owing to the defect inspection of CCM by the semiskilled work the average inspection time of CCM takes about 40 to 50 seconds. As time goes by the efficiency takes a sudden turn for the worse because workers must inspect with seeing a monitor directly. In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of assembled CCM. The performances of the developed inspection system and its algorithm are tested on many samples. Experimental results reveal that the proposed system can focus the lens of CCM within 5s and we can recognize various types of defect of CCM modules with good accuracy and high speed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1416-1423
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• 2017

Lane detection technology is one of the most important issues on car safety and self-driving capability of autonomous vehicle. This paper introduces an accurate lane detection scheme based on OCC(Optical Camera Communication) for moving vehicles. For lane detection of moving vehicles, the streetlights and the front camera of the vehicle were used for a transmitter and a receiver, respectively. Based on the angle information of multiple streetlights in a captured image, the distance from sidewalk can be calculated using non-linear regression analysis. Simulation results show that the proposed scheme shows robust performance of accurate lane detection.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2359-2364
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• 2017

This paper proposes a scale factor based range estimation method using a sum of squares (SOS) method. Many previous studies measured distance by using a camera, which usually required two cameras and a long computation time for image processing. To overcome these disadvantages, we propose a range estimation method for an object using a single moving camera. A SOS-based Luenberger observer is proposed to estimate the range on the basis of the Euclidean geometry of the object. By using a scale factor, the proposed method can realize a faster operation speed compared with the previous methods. The validity of the proposed method is verified through simulation results.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.26 no.6
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• pp.493-501
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• 2013

LED lighting is sensitive because it made by semiconductor. So it has been researched about radiation of heat technologies for a long time. In addition, measurement and assessment a radiation of heat also conducted. It is necessary to get a date of accuracy temperature on the board after LED driven for measuring Junction temperature of the LED Lighting. For this research, we use 5 chip which is 4 W power on top of LED lighting board made by aluminum. Thermal camera effects to emissivity depending on material and property of the surface in LED board because it determines thermal energy which emitted from material surface. it is not only thermal camera has not a standard about emissivity. It has an error of temperature when emissivity was measured by thermal camera. we confirmed that emissivity and reflected temperature depending on color and quality of the surface throughout experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.2
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• pp.165-177
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• 1996

This paper presents a navigation method for a mobile robot which can follow a path drawn on a monitor screen. The current position and heading direction of the mobile robot are obtained using a single camera from a single image of the guide mark projected on a convex mirror. This proposed method eliminates the need to rotate or tilt the camera to track the guide mark, because the convex mirror and a stationary camera provide a panoramic view of the surrounding area. As guide marks, fluorescent lamps on the ceiling, door frames, or any other natural line segment can be used without adding any artificial elements to them.

• International Journal of Contents
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• v.6 no.4
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• pp.49-56
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• 2010

In this paper we present a system that enables the user to interact with large display system even without touching the screen. With two infrared sensitive cameras mounted on the bottom left and bottom right of the display system pointing upwards, the user fingertip position on the selected region of interest of each camera view is found using vertical intensity profile of the background subtracted image. The position of the finger in two images of left and right camera is mapped to the display screen coordinate by using pre-determined matrices, which are calculated by interpolating samples of user finger position on the images taken by pointing finger over some known coordinate position of the display system. The screen is then manipulated according to the calculated position and depth of the fingertip with respect to the display system. Experimental results demonstrate an efficient, robust and stable human computer interaction.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.9-14
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• 2020

It is necessary to apply a non-contact high-speed scanning system that can measure in real time in order to prevent the dropping and deformation of the main parts of railway vehicles during high-speed running. Recently, research on a scanning system that detects the deformation state of main parts from a video image taken using a high-performance camera has been actively pursued. In this study, we researched an analysis algorithm of a high-speed scanning system that uses a high-performance camera to monitor the deformation and drop-out state of the main components of the running units equipment in real time.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.75-81
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• 2020

Approximately 1.3 million people die from traffic accidents each year, and smartphone usage while driving is one of the main causes of such accidents. Therefore, detection of smartphone usage by drivers has become an important part of distracted driving detection. Previous studies have used single camera-based methods to collect the driver images. However, smartphone usage detection by employing a single camera can be unsuccessful if the driver occludes the phone. In this paper, we present a driver smartphone usage detection system that uses multiple cameras to collect driver images from different perspectives, and then processes these images with ensemble convolutional neural networks. The ensemble method comprises three individual convolutional neural networks with a simple voting system. Each network provides a distinct image perspective and the voting mechanism selects the final classification. Experimental results verified that the proposed method avoided the limitations observed in single camera-based methods, and achieved 98.96% accuracy on our dataset.