• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.463-470
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• 2008

In this paper, we confirm that the two properties, 'existence of obstacles' and 'connectivity between obstacles', involved in information acquired by a robot can be used efficiently for location recognition of the robot by using rough sets. Moreover, we propose a method which can reduce ambiguity of the location recognition by applying the properties and recognize the robot's location with distrustful information of the environment where the robot moves. We confirmed it through computer simulation that a robot moves to a goal with only the map containing not enough information on the real environment.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.109-114
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• 2005

Many researchers have been interested in user authentication using biometric information, and face recognition is a lively field of study of ones in the latest biometric recognition field because of advantage that it can recognize who he/she is without touching machinery. This paper proposes method to extract eye location effectively at face detection step that is precedence work of face recognition. The iterative threshold selection was adopted to get a proper binary image and also the Gaussian filter was used to intensify the properties of eyes to extract an eye location. The correlation was adopted to verify if the eye location is correct or not. Extraction of an eye location that propose in paper as well as accuracy, considered so that may can apply to online system and showed satisfactory performance as result that apply to on line system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.29-35
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• 2014

The formula contains up between the text and the structural information, as well as their mathematical symbols. Research on-line or off-line recognition formula is underway actively used in various fields, and various forms of the equation are implemented recognition system. Although many documents are included in the various formulas, it is not easy to enter a formula into the computer. Recognition of the expression is divided into two processes of symbol recognition and structural analysis. After analyzing the location information of each character is specified to recognize the effective area after each symbol, and to the structure analysis based on the proximity between the characters is recognized as an independent single formula. Furthermore, analyzing the relationship between the front and back each time a combination of the position relationship between each symbol, and then to add the symbol which was able to easily update the structure of the entire formula. In this paper, by using a scanner to scan the book formula was used to interpret the meaning of the recognized symbol has a relative size and location information of the expression symbol. An algorithm to remove the formulas for calculation of the number of formula is present at the same time is proposed. Using the proposed algorithms to scan the books in the formula in order to evaluate the performance verification as 100% separation and showed the recognition rate equation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.473-480
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• 2013

In this paper, location recognition algorithm is developed to improve the accuracy using improve Trilateration. The location recognition algorithm is first calculate the location refer to the measured signal power. Error can be occurred when measure distance with arranged node in specific location. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. Second, we apply algorithm of section filtering. If there are 4 sections in node, we consider 1 section to 6 location recognition coordinates. A special characteristic drawback of RF is that the actual distance is actually farther than the calculated received distance data. This is error is incurred when the signal strength increases. We reduce the location recognition error by applying an improved algorithm as secondary after filtering primary through section filtering.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.162-170
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• 2012

It is very important for the robot to recognize its position to accomplish numerous tasks and to go to the goal. In this paper, we suggest Location Recognition System to distinguish robot's locations using land-mark and the odometer in the environment of sensor network. All in all, we created a basic intelligent robot, Location Recognition System, and Environment Sensor Modules; we verified the proposed algorithm through computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.725-732
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• 2011

There are some trials to adopt the RFID/USN technologies at container terminals for effective terminal operations. In this paper, we propose a realtime location recognition method for stacked containers under the assumption that each container has a wireless sensor node to measure the RSSI values from neighbor nodes. We develope an RSSI based location algorithm with performance evaluations by RSSI measurement and application program implementation.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.569-577
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• 2016

Place recognition for LBS (Location Based Service) has been one of the important techniques for user-oriented service. FLANN (Fast Library for performing Approximate Nearest Neighbor) of place recognition with image features is fast, but it is affected much by environmental condition such as occlusions. This paper presents a place recognition method using quad vocabulary tree with SURF (Speeded Up Robust Features). In learning stage, an image is represented with spatial pyramid of three levels and vocabulary trees of their sub-regions are constructed. Query image is matched with the learned vocabulary trees in each level. The proposed method measures homography error of the matched features. By considering the number of inliers in sub-region, we can improve place recognition performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1058-1065
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• 2010

In the recent, the importance of ubiquitous-related technique is increased as many companies and researchers make an effort to create a new service model using ubiquitous computing and network technologies. Especially, the research of indoor location recognition has gained a lot of interest because it is a critical component for supporting ubiquitous services. Nevertheless, the simulation tool for indoor location recognition hardly has studied compared to their importance. In this paper, we propose a Ptolemy-based simulator over UWB channel that provides short-range and high-bandwidth communication. Finally, we conduct experiments using the proposed simulator and analyze the performance of various location recognition algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.11-17
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• 2008

This paper proposes the USN node location recognition method with low power, which is the modified centroid method. The conventional Zigbee node location recognition is used to the three RSSI values from three beacons, respectively. When a person move with node, the moving speed of USN node doesn't fast. Therefore, one among three positions used to the value that it is a previous value. This method doesn't large the error in terms of the exact position. Using hand-off method, we get about 30% power advantage than the conventional centroid method. And Our monitoring system add the function that it is possible to search for the node region by color.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.12-21
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• 2010

In this paper, we suggest Location Recognition System using Sensor Network; it distinguishes locations. Furthermore, this paper proposes Intelligent Navigation System which presents the proper route for the user. INS evaluates the user's preference, tendency and environmental state using Sensor Network Module and current driving information. This system also uses Soft-computing method to learn and infer the person’s preference and tendency. This paper defines Intelligent Assistance Module (IAM) which is a connector in between a user and a robot; it is portable. All in all, we created a basic intelligent robot, Location Recognition System, and Environment Sensor Modules; we verified the proposed algorithm through computer simulations.