• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1393-1404
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• 1995

For the factory automation(FA) of production or assembly lines, computer vision techniques have been widely used for the recognition and position-control of objects. In this application, it is very important to analyze characteristic features of each object and to find an efficient matching algorithm using the selected features. If the object has regular or homogeneous patterns, the problem is relatively simple. However, If the object is shifted or rotated, and if the depth of the input visual system is not fixed, the problem becomes very complicated. Also, in order to understand and recognize objects with concentric noise patterns, it is more effective to use feature-information represented in polar coordinates than in cartesian coordinates. In this paper, an algorithm for the recognition of objects with concentric circular noise-patterns is proposed. And position-conrtol information is calculated with the matching result. First, a filtering algorithm for eliminating concentric noise patterns is proposed to obtain concentric-feature patterns. Then a shift, rotation and scale invariant alogrithm is proposed for the recognition and position-control of objects uusing invariant feature information. Experimental results indicate the effectiveness of the proposed alogrithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.713-716
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• 2009

In this paper, we propose a vision-based detection of container hole for container location measuring. We use a method for container position using detection of diagonal container holes, because containers have holes that are linked to spreader headblocks. First, we extract images from spreader and detect straight lines to detect container in images using hough transform. Next, proposed method finds positions of cross at the right angles and set candidates of the corner that is linked to spreader headblocks. Finally, this method performs template matching to detect a right corner of containers. Experimental results show that proposed method performed well at detection of container position.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.171-179
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• 2004

Today, the number of vehicle increased rapidly with the development of modem science technology, and it caused serious problems; traffic jam, accident and pollution etc. One of the solve methods these problems it is necessary to develope the vehicle navigation systems and it is already widely used to in field of military etc. Vehicle navigation system can increase the efficiency of traffic flow and offer at a drivers at a best driving conditions. In the vehicle navigation, most important thing is to measure of correct position. There are classifiable as three types. The first is G.P.S., method at artificial satellites which measures the present position and velocity any time, any where in the world at the same time. Secondly, a vehicle can determine its position and path information with a gyroscope and odometer signal, which is called Dead-Reckoning method. Thirdly, hybrid navigation system is the combined of two methods to make utilize the advantage of each navigation system. In the paper, we are analyzed to characteristics at a gyro sensor and introduce at a composition of hybrid navigation system which is combined with the G.P.S., D.R., and map-matching technique. We analyze deeply for the Map-Matching method and explain the coordinate transformation for G.P.S., and the Hybrid navigation algorithm is developed and experimented. Finally, we conclude and comment about our road test results.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.67-77
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• 2021

Spatial data is becoming very important as a medium that connects various data produced in smart cities, digital twins, autonomous driving, smart construction, and other applications. In addition, the rapid construction and update of spatial information is becoming a hot topic to satisfy the diverse needs of consumers in this field. This study developed a software prototype that can match the position of an image-based 3D building model produced without Ground Control Points using existing spatial data. As a result of applying this software to the test area, the 3D building model produced based on the image and the existing spatial data show a high positional matching rate, so that it can be widely used in applications requiring the latest 3D spatial data.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.79-84
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• 2010

Matching spots between two sets of 2-dimensional electrophoresis can make it possible to find out the generation, extinction and change of proteins. Generally protein spots are separated by 2-dimensional electrophoresis. This process makes the position of the same protein spot a little different according to the status of the tissue or the experimental environment. Matching the spots shows that the relation of spots is non-uniform and non-linear transformation. However we can also find that the local relation preserves the topology. This study proposes a matching method motivated by the preservation of the topology. To compare the similarity of the topology, we compared the distance and the angle between neighbour spots. Experimental result shows that the proposed method is effective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1123-1133
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• 1999

In this paper, we applied mode matching and generalized scattering matrix methods to three plane mode matching method for analyzing T-junctions. We calculated all scattering matrix elements by only three times and considered several incident modes. By proposed analysis method, we could analyze various waveguide discontinuity structures more conveniently and accurately. Using the stepped T-junction, we would be able to reduce the reflection coefficient at an input port and use it over wider band. Simulated and HFSS data of T-junctions are compared, showing good agreement for scattering matrix elements. Considering step numbers, height, length and position, we extracted for optimum dimensions and equivalent circuit parameters.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.361-367
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• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.447-451
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• 2011

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purposes such as CAN and MOST. Especially, the MOST network is usually adapted to provide entertainment service. The car navigation system is also widely used for guiding driving paths to driver. The position for the navigation system is usually acquired by GPS technology. However, the GPS technique has two serious problems. The first is unavailability in urban canyons. The second is inherent positional error rate. The problems have been studied in many literatures. However, the second still leads to incorrect locational information in some area, especially parallel roads. This paper proposes a performance tuning method of image matching algorithm for the car navigation system. The method utilizes images obtained from in-vehicle MOST network and a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. In order to accuracy improvement of image matching algorithm, three conditions are applied. The experimental tests show that the proposed system increases the accuracy.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.415-425
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• 2007

This paper proposes a method of underwater source localization using the wideband interference patterns matching. By matching two interference patterns in the spectrogram, it is estimated a ratio of the range from source to sensor5, and then this ratio is applied to the Apollonius circle. The Apollonius circle is defined as the locus of all points whose distances from two fixed points are in a constant value so that it is possible to represent the locus of potential source location. The Apollonius circle alone, however still keeps the ambiguity against the correct source location. Therefore another equation is necessary to estimate the unique locus of the source location. By estimating time differences of signal arrivals between source and sensors, the hyperbola equation is used to get the cross point of the two equations, where the point being assumed to be the source position. Simulations are performed to get performances of the proposed algorithm. Also, comparisons with real sea experiment data are made to prove applicability of the algorithm in real environment. The results show that the proposed algorithm successfully estimates the source position within an error bound of 10%.