• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.553-559
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• 2020

In order to prevent subsidence in urban areas, which is a major cause of damage to aging underground facilities, an integrated underground space map is being produced for systematic management of underground facilities. However, there is a problem of delaying the update time because an unupdated underground facility object is included in the process of updating the underground space integrated map. In this paper, we proposed a method to shorten the update time of the integrated map by selecting only the updated objects required for the update process of the underground space integrated map based on the central point of the underground facilities. Through the comparison of the centroid, the number of search targets is greatly reduced to shorten the search speed, and the distance of the actual location values between the two objects is calculated whether or not the objects are the same. The proposed method shows faster performance as the number of data increases, and the updated object can be reflected in the underground space integrated map about four times faster than the existing method.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.200-205
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• 2002

In this paper, we propose an object tracking system which extracts moving areas+ shaped on objects in video sequences and decides tracks of moving objects. Color invariances are exploited to extract the plausible object blocks and the degree of radial homogeneity is utilized as local block feature to find out the block correspondences.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.405-408
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• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.279-284
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• 2008

We propose the iconic animation of the software requirement specifications by using the object and dynamic models of the object modeling technique(OMT) methodology. In order to produce the iconic animation, we use "graphical classes" and "icon transformations." In general, the graphical classes are defined for each class of the object diagram. The icon transformations which show the activities of the application are constructed by considering the meaning of the activities and are defined by either basic or compound icons. The icon transformations are added to the state diagrams to generate extended state diagrams. The animation system generates the header files and the code instantiating GUI from the object diagram having graphical classes. The system also generates "event methods" from the extended state diagrams. When the event methods are executed, the behavior of the events is animated by the icon transformations.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.142-150
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• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• ETRI Journal
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• v.26 no.2
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• pp.122-135
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• 2004

Although frame-based MPEG-4 video services have been successfully deployed since 2000, MPEG-4 video coding is now facing great competition in becoming a dominant player in the market. Object-based coding is one of the key functionalities of MPEG-4 video coding. Real-time object-based video encoding is also important for multimedia broadcasting for the near future. Object-based video services using MPEG-4 have not yet made a successful debut due to several reasons. One of the critical problems is the coding complexity of object-based video coding over frame-based video coding. Since a video object is described with an arbitrary shape, the bitstream contains not only motion and texture data but also shape data. This has introduced additional complexity to the decoder side as well as to the encoder side. In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efficient coding technologies that reduce the complexity of the encoder. Using the proposed coding schemes, we have obtained a 56 percent reduction in shape-coding complexity over the MPEG-4 video reference software (Microsoft version, 2000 edition).

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.165-166
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• 2014

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.99-115
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• 2003

In this paper, we present a knowledge-based object-oriented spatial database system called KOBOS. A knowledge-based approach is introduced to the object-oriented spatial database system for data modeling and approximate query answering. For handling the structure of spatial objects and the approximate spatial operators, we propose three levels of object-oriented data model: (1) a spatial shape model; (2) a spatial object model; (3) an internal description model. We use spatial type abstraction hierarchies(STAHs) to provide the range of the approximate spatial operators. We then propose SOQL, a spatial object-oriented query language. SOQL provides an integrated mechanism for the graphical display of spatial objects and the retrieval of spatial and aspatial objects. To support an efficient hybrid query evaluation, we use the top-down spatial query processing method.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.284-288
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• 2010

Video surveillance is widely used in establishing the societal security network. In this paper, intrusion detection based on visual information acquired by static camera is proposed. Proposed approach uses background model constructed by approximated median filter(AMF) to find a foreground candidate, and detected object is calculated by analyzing motion information. Motion detection is determined by the relative size of 2D object in RGB space, finally, the threshold value for detecting object is determined by heuristic method. Experimental results showed that the performance of intrusion detection is better one when the spatio-temporal candidate informations change abruptly.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.232-241
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• 2014

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.