• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.22-32
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• 2022

Optical character recognition is a primary technology required in different fields, including digitizing archival documents, industrial automation, automatic driving, video analytics, medicine, and financial institution, among others. It was created in 1928 using pattern matching, but with the advent of artificial intelligence, it has since evolved into a high-performance character recognition technology. Recently, methods for detecting curved text and characters existing in a complicated background are being studied. Additionally, deep learning models are being developed in a way to recognize texts in various orientations and resolutions, perspective distortion, illumination reflection and partially occluded text, complex font characters, and special characters and artistic text among others. This report reviews the recent deep learning-based text detection and recognition methods and their various applications.

• Journal of Environmental Science International
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• v.29 no.4
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• pp.361-369
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• 2020

With the increasing role of environmental design in promoting urban safety, new design attempts have been made to improve pedestrian safety in crosswalks. This study proposes an evidence-based design solution for improving crosswalk function by conducting simulations and field experiments. Drivers with more than one-year driving experience participated in this study. Four different crosswalk design patterns were prepared: (1) a zebra pattern, (2) zebra pattern with colored triangles, (3) 3D pattern, and (4) art pattern with unique colors and design. The results supported that the zebra pattern with colored triangles could be the most effective solution for crosswalk design by increasing visibility, attention, deceleration, and landscape aesthetics. This study provided objective data to support the performance of various crosswalk patterns and suggested the need to reevaluate the present crosswalk design guidelines.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.369-375
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• 2008

The kinematics and control problem of a visual alignment system is investigated, which plays a crucial role in the fabrication process of flat panel displays. The first solution is the inverse kinematics of a 4PPR parallel alignment mechanism. It determines the driving distance of each joint to compensate the misalignment between mask and panel. Second, an efficient vision algorithm for fast alignment mark recognition is suggested, where by extracting essential feature points to represent the geometry of a mark, the geometric template matching enables much faster object recognition comparing with the general template matching. Finally, the overall visual alignment process including the kinematic solution, vision algorithm, and joint control is implemented and experimental results are given.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.215-218
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• 2002

Gesture recognitions needed for various applications and is now gaining in importance as one method of enabling natural and intuitive human machine communication. In this paper, we propose a real time hand-signal recognition system in 3-dimensional space performs robust, real-time tracking under varying illumination. As compared with the existing method using classical pattern matching, this system is efficient with respect to speed and also presents more systematic way of defining hand-signals and developing a hand-signal recognition system. In order to verify the proposed method, we developed a virtual driving system operated by hand-signals.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.138-144
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• 2014

Now, Autonomous unmanned vehicle has become an issue in next generation technology. 2D Laser scanner as the distance measurement sensor is used. 2D Laser scanner detects the distance of 80m, measured angle is -5 to 185 degree. Laser scanner detects only the plane, but using motor swings. As a result, traffic signs detect and analyze patterns. Traffic signs when driving at low speed, shape of the detected pattern is very similar. By shaking the laser scanner, traffic signs and other obstacles became clear distinction.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.12-20
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• 2007

The aiming ability is a key to improve the accuracy performance of the gun pointing system in the ground military vehicle. This paper describes the new detection method of chatter vibration using disturbance acceleration in the pointing structure. In order to analysis the vibration trends of the pointing system occurred while the vehicle driving, acceleration data obtained from vehicle was processed by using data processing algorithm with moving average and Hilbert transform. The specific mode constants of acceleration were obtained from various disturbances. Vehicle velocity, road condition and property of pointing structure were considered as factors which make the change of vibration trend in vehicle dynamics. Finally, back propagation neural networks have been applied to the pattern recognition of the classification of vibration signal in various driving conditions. Results of signal processing were compared with other condition result and analysed.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1833-1840
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• 2013

A golf ball collecting robot in a golf ball driving range has been recently required because it is safer and more economic than a human being. In this paper, the golf ball recognition and distance estimation system based on a neural network and OpenCV is developed for the robot. The simulation results show that the recognition ratio is over 87% for the distance of less than 120cm and accurate rate for distance estimation is over 85% for golf balls in 30-180cm from a webcam.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.66-72
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• 2016

As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.78-80
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• 2005

The pattern recognition of automobile and parking line for the automatic car parking system was processed based on statistical method for reducing the processing time. The command of driving for parking at the vacant parking lot was transmitted from processor to motor driven actuator using direct sequence spread spectrum communication, which enables the multiple transmission in CAN(controller area network). The test-bed which has CCD camera, processor, radio transceiver and FPGA was implemented and demonstrated to be operated well.