• Proceedings of the KSR Conference
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• 2003.10c
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• pp.587-593
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• 2003

There has been much interest in the Bluetooth technology since it could enable users to connect to a wide range of computing and telecommunication devices without the need to carry or connect cables. It delivers opportunities for rapid, ad-hoc connections, and in the future, could possibly enable automatic, unconscious, connections between devices. In this paper, we discussed a scatternet formation protocol for Bluetooth-based ad hoc networks and proposed the identification system of an object using Bluetooth Scatternets. Over the past few years, several studies have been made on the identification of an object by several RF(Radio Frequency) systems. But there are still some problems, the interference of signals as an example, for the identification of an object. The critical question is how to identify an object precisely without the interference of signals. This paper is an investigation of the Scatternet formation protocol for Bluetooth-based ad hoc networks and the identification system of an object using Bluetooth Scatternets composed of multiple Piconets.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.145-148
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• 1996

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2693-2706
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• 1999

Reengineering to object-oriented system is needed to maintain the system and satisfy requirements of structure change. Target systems which should be reengineered to object-oriented system are difficult to change because these systems have no design document or their design document is inconsistent of source code. Using design document to identifying objects for these systems is improper. There are several researches which identify objects through procedural source code analysis. In this paper, we propose automatic object identification method based on clustering of VTFG(Variable-Type-Function Graph) which represents relations among variables, types, and functions. VTFG includes relations among variables, types, and functions that may be basis of objects, and weights of these relations. By clustering related variables, types, and functions using their weights, our method overcomes limit of existing researches which identify too big objects or objects excluding many functions. The method proposed in this paper minimizes user's interaction through automatic object identification and make it easy to reenginner procedural system to object-oriented system.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.51-58
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• 2017

Because of safety and security, Surveillance camera market is growing. Accordingly, Study on video recognition and tracking is also actively in progress, but There is a limit to identify object by obtaining the information of object identified and tracked. Especially, It is more difficult to identify multiple objects in open space like shopping mall, airport and others utilized surveillance camera. Therefore, This paper proposed adding object identification function by using RFID to existing video-based object recognition and tracking system. Also, We tried to complement each other to solve the problem of video and RFID based. Thus, through the interaction of system modules We propose a solution to the problems of failing video-based object recognize and tracking and the problems that could be cased by the recognition error of RFID. The system designed to identify the object by classifying the identification of object in four steps so that the data reliability of the identified object can be maintained. To judge the efficiency of this system, this demonstrated by implementing the simulation program.

• ETRI Journal
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• v.25 no.2
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• pp.121-132
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• 2003

To enhance the productivity of software development and accelerate time to market, software developers have recently paid more attention to a component-based development (CBD) approach due to the benefits of component reuse. Among CBD processes, the identification of reusable components is a key but difficult process. Currently, component identification depends mainly on the intuition and experience of domain experts. In addition, there are few systematic methods or tools for component identification that enable domain experts to identify reusable components. This paper presents a systematic method and its tool called a component identifier that identifies software components by using object-oriented domain information, namely, use case models, domain object models, and sequence diagrams. To illustrate our method, we use the component identifier to identify candidates of reusable components from the object-oriented domain models of a banking system. The component identifier enables domain experts to easily identify reusable components by assisting and automating identification processes in an earlier development phase.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.4
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• pp.381-392
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• 2003

Component-based Development(CBD) based on the software reuse has been more attractive from software companies that want to enhance software productivity. However, since component identification process is mainly dependent on domain expert´s intuition and experience, it was very difficult to develop tools for supporting the component identification process. In this paper, we propose a systematic procedure of identifying reusable component by using object dependencies and object usages and provide a design and implementation of its supporting tool. In object-oriented domain models. there exists several diagrams which are described in different viewpoints. From these diagrams, object dependency and object usages are extracted and merged into an object dependency network, which is a basis for performing a comfonent identification algorithm. Finally, through a case study of internet banking system, we evaluate the applicability of the proposed identification process and tool.

• The Journal of Industrial Distribution & Business
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• v.8 no.7
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• pp.51-61
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• 2017

Purpose - Present study investigates character identification and emotional response to character that may affect consumers' intention to purchase the character-attached products. And this study explores whether symbolic relevance and object relevance affect the character identification, and whether character attractiveness and character salience affect the emotional response to characters. Research design, data, and methodology - SNS characters, animated characters, game characters, and traditional characters were used as experimental characters. And stationery as experimental product was used. 250 college students participated in the empirical study, and structural equation model was used to verify hypotheses. Results - First, the character identification and emotional response to characters affected the intention to purchase the products positively, and the emotional response to characters also positively affected character identification; second, symbolic relevance had no positive impact upon character identification, while object relevance had positive influence on character identification; and third, character attractiveness and salience had a positive effect on the emotional response. Conclusions - Present study contributes to the progress of character theories. Marketers should find ways to increase consumers' object relevance to characters and the level of characters' attractiveness and salience in order to promote the intent to purchase the products.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.522-531
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• 2016

In this study, we propose an object identification method for bin-picking developed for industrial robots. We identify the grasp posture and the associated geometric parameters of grasp objects using the joint data of a robotic gripper. Prior to grasp identification, we analyze the grasping motion in a low-dimensional space using principle component analysis (PCA) to reduce the dimensions. We collected the joint data from a human hand to demonstrate the grasp-identification algorithm. For data acquisition of the human grasp data, we conducted additional research on the motion characteristics of a human hand. We explain the method for using the algorithm of grasp identification for bin-picking. Finally, we present a subject for future research using our proposed algorithm of grasp model and identification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.