• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.208-211
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• 2004

Landmark matching is one of an important algorithm for navigation of satellite images. This paper proposes a fast landmark matching algorithm using a MGLI (Moving Guide-Line Image). For searching the matched point between the landmark chip and a part of image, correlation matrix is used generally, but the full-sized correlation matrix has a drawback requiring plenty of time for matching point calculation. MGLI includes thick lines for fast calculation of correlation matrix. In the MGLI, width of the thick lines should be determined by satellite position changes and navigation error range. For the fast landmark matching, the MGLI provides guided line for a landmark chip we want to match, so that the proposed method should reduce candidate areas for correlation matrix calculation. This paper will show how much time is reduced in the proposed fast landmark matching algorithm compared to general ones.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.642-645
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• 1991

This paper presents the results of research on hardware and software of the landmark tracking system to the positions of moving robot in real time. The landmark tracking system is composed of CCD camera, landmark, strobo system and image processing board. The algorithm calculates the position and direction by using the coordinate transformation fomula after calculating the centroid and rotation angle of landmark at fixed position using the image data. The experiment is performed with landmark tracking system is loaded on xyz-table. XYZ-table is used for identifying the true position in our experiment. The results shows that this system has high performance with maxima error of .+-.1 pixels.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.68-75
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• 2011

This paper addresses an underwater landmark for updating UUV positioning information. A method is proposed in which the landmark's cubic shape and edge are recognized. The reliability, installation load, and management of landmark design were taken into consideration in order to assess practical applications of the landmark. Landmark recognition was based on topological features. The straight line recognition confirmed the landmark's location and enabled an UUV to accurately estimated its underwater position with respect to the landmark. An efficient recognition method is proposed, which provides real-time processing with limited UUV computing power. An underwater experiment was conducted in order to evaluate the proposed method's reliability and accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.164-169
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• 2009

As one of the most interesting scenes, landmarks constitute a large percentage of the vast amount of scene images available on the web. On the other hand, a specific "landmark" usually has some characteristics that distinguish it from surrounding scenes and other landmarks. These two observations make the task of accurately estimating geographic information from a landmark image necessary and feasible. In this paper, we propose a method to identify landmark location by means of landmark recognition in view of significant viewpoint, illumination and temporal variations. We use GPS-based clustering to form groups for different landmarks in the image dataset. The images in each group rather fully express the possible views of the corresponding landmark. We then use a combination of edge and color histogram to match query to database images. Initial experiments with Zubud database and our collected landmark images show that is feasible.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.473-479
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• 2009

This paper proposes an efficient method to locate the automated guided vehicle (AGV) into a specific parking position using artificial visual landmark and vision-based algorithm. The landmark has comer features and a HSI color arrangement for robustness against illuminant variation. The landmark is attached to left of a parking spot under a crane. For parking, an AGV detects the landmark with CCD camera fixed to the AGV using Harris comer detector and matching descriptors of the comer features. After detecting the landmark, the AGV tracks the landmark using pyramidal Lucas-Kanade feature tracker and a refinement process. Then, the AGV decreases its speed and aligns its longitudinal position with the center of the landmark. The experiments showed the AGV parked accurately at the parking spot with small standard deviation of error under bright illumination and dark illumination.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.418-420
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• 1993

In this paper, we proposed a new FMS Landmark recognition algorithm using color images. Firstly, a NTSC image fame is captured, and then it is converted to a field image in order to reduce the image blurring from the AGV motion. Secondly, the landmark is detected via the comparison of the color vectors of image pixels with the landmark color. Finally, the identification of FMS landmark is executed using a newly designed landmark pattern with a set of reference points. The landmark pattern is normalized against its translation, rotation, and scaling. And then, its vertical projection data are fisted for the pattern classification using the standard data set. Experimental results show that our scheme performs well.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.749-757
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• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.1-41
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• 2002

This paper describes a robust landmark matching method to reduce ambiguity of candidate of landmark. General robot system acquires the candidate of landmark through vision sensor in outdoor environment. Our robot uses the omnidirectional vision system to get all around the view. Thus, the robot obtains more candidates of landmark than the conventional vision system. To obtain the candidates of landmark, robot uses the two types of feature. They are vertical edge and merged region of vertical edges. The former is to extract the vertical line of building, street lamp, etc. The latter is to reduce ambiguity of vertical edge in similar region. It is difficult to match the candidates of landmark...

• Journal of the Korean Society of Industry Convergence
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• v.14 no.3
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• pp.105-111
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• 2011

Landmark Spots in 2D gel electrophoresis are used in many methods of 2DEG spot matching. Landmark Spots are obtained manually and it is a bottle neck in the entire protein analysis process. Automated landmark spots detection is a very crucial topic in processing a massive amount of 2DGE data. In this paper, Automated landmark spot detection is proposed using point pattern matching and graph theory. Neighbor spots are defined by a graph theory to use and only a centered spot and its neighbor spots are considered for spot matching. Normalized Hausdorff distance is introduced as a criterion for measuring degree of similarity. In the conclusion, the method proposed in this paper can get about 50% of the total spot pairs and the accuracy rate is almost 100%, which the requirements of landmark spots are fully satisfied.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.123-128
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• 2012

In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.