• Journal of Institute of Control, Robotics and Systems
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• 제11권1호
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• pp.67-76
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• 2005

In this paper, An analysis on the intelligence system for a biped walking robot(BWR) was made and its results were applied to the BWR. Various sensors were applied to the developed BWR for autonomous and intelligent walk in unknown environments. To measure the distance between the object and BWR, ultrasonic sensor and infrared-rays sensor were used. To identity surrounding environments, vision system was used. Gyro sensor was used to control the posture of BWR. Also, piezoelectricity sensor was used to identity the pressure of foot landing on the surface. Sensors applied to the robot have measurement errors according to noises or walking environments. To improve the function of these sensors, influences of noise or sensing errors were minimized using a sensor fusion scheme. A gait test using the sensor fusion system was performed, and its results are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2000년도 춘계종합학술대회
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• pp.320-324
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• 2000

In this paper we propose and realize the large scale multimedia security system that one janitor control many rooms in many building on multimedia. We Study the system that one watch janitor lots of rooms and lots of buildings the same time, and store the trespasser's moving cource in Database for understanding his action pattern using computer vision technology, but the relational system cannot solve the problem that the trespasser disjoint the security system on sensing method and the system watch only one room or one building.

• The Transactions of the Korean Institute of Electrical Engineers P
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• 제65권1호
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• pp.66-71
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• 2016

According to the development of depth sensing devices and depth estimation technology, depth information becomes more important for object detection in computer vision. In terms of recognition rate, pedestrian detection methods have been improved more accurately. However, the methods makes slower detection time. So, many researches have overcome this problem by using GPU. Here, we propose a real-time pedestrian detection algorithm that does not rely on GPU. First, the depth-weighted distance map is used for detecting expected human regions. Next, human detection is performed on the regions. The performance for the proposed approach is evaluated and compared with the previous methods. We show that proposed method can detect human about 7 times faster than conventional ones.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.267-269
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• 2009

Incomplete knowledge instances may be registered from misidentifications of sensors, such as vision sensor. In previous study, we proposed robust object instance registration method to robot centered knowledge framework to guarantee the consistency of the registered knowledge. In real environment, a persistent update is necessary due to the objects can be moved dynamically. In this paper, we propose the way to update robot knowledge continually using the registration method. Our experiment in this paper shows that sound and complete knowledge can be registered and updated by the proposed method, even under imperfect sensing data.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.137-140
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• 2008

Recently many areas require wide field of view images. Such as surveillance, virtual reality, navigation and 3D scene reconstruction. Conventional camera systems have a limited filed of view and provide partial information about the scene. however, omni directional vision system can overcome these disadvantages. Acquiring 360 degree panorama images requires expensive omni camera lens. In this study, 360 degree panorama image was tested using a low cost optical reflector which captures 360 degree panoramic views with single shot. This 360 degree panorama image system can be used with detailed positional information from GPS/INS. Through this study result, we show 360 degree panorama image is very effective tool for mobile monitoring system.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제57권2호
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• pp.320-326
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• 2008

In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.

• Agricultural and Biosystems Engineering
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• 제1권2호
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• pp.88-94
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• 2000

Nitrogen (N) management is critical for corn production. On the other hand, N leaching into the groundwater creates serious environmental problems. There is a demand for sensors that can assess the plant N deficiency throughout the growing season to allow producers to reach their production goals, while maintaining environmental quality. This paper reports on the performance of a vision-based reflectance sensor for real-time assessment of N stress level of corn crops. Data were collected representing the changes in crop reflectance in various spectral ranges over several stages of development in the growing season. The performance of this non-contact sensor was validated under various field conditions with reference measurement from a Minolta SPAD meter and stepped nitrogen treatments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.76-76
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• 2000

The calibration of the robot system with a visual sensor consists of robot, hand-to-eye, and sensor calibration. This paper describe a new technique for computing 3D position and orientation of a 3D sensor system relative to the end effect of a robot manipulator in an eye-on-hand robot configuration. When the 3D coordinates of the feature points at each robot movement and the relative robot motion between two robot movements are known, a homogeneous equation of the form AX : XB is derived. To solve for X uniquely, it is necessary to make two robot arm movements and form a system of two equation of the form: A$_1$X : XB$_1$ and A$_2$X = XB$_2$. A closed-form solution to this system of equations is developed and the constraints for solution existence are described in detail. Test results through a series of simulation show that this technique is simple, efficient, and accurate fur hand/eye calibration.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.508-511
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• 2007

Car navigation system is one of the most important applications in telematics. A newest trend of car navigation system is using real video captured by camera equipped on the vehicle, because video can overcome the semantic gap between map and real world. In this paper, we suggest a visual car navigation system that visually represents navigation information or route guidance. It can improve drivers' understanding about real world by capturing real-time video and displaying navigation information overlaid on it. Main services of the visual car navigation system are graphical turn guidance and lane change guidance. We suggest the system architecture that implements the services by integrating conventional route finding and guidance, computer vision functions, and augmented reality display functions. What we designed as a core part of the system is visual navigation controller, which controls other modules and dynamically determines visual representation methods of navigation information according to a determination rule based on current location and driving circumstances. We briefly show the implementation of system.

• Proceedings of the KIEE Conference
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.974-976
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• 1995

Segmentation of image data is an important problem in computer vision, remote sensing, and image analysis. Most objects in the real world have textured surfaces. Segmentation based on texture information is possible even if there are no apparent intensity edges between the different regions. There are many existing methods for texture segmentation and classification, based on different types of statistics that can be obtained from the gray-level images. In this paper, we use a neural network model --- ART-2 (Adaptive Resonance Theory) for textures in an image, proposed by Carpenter and Grossberg. In our experiments, we use Walsh matrix as feature value for textured image.