• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1123-1124
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• 2008

In this paper, we develop a program that recognition of the object 3D pose using stereo camera. In order to detect the object, this paper is applied to canny edge detection algorithm and also used stereo camera to get the 3D point about the object and applied to recognize the pose of the object using iterative closest point(ICP) algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.558-566
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• 2000

Object recognition is a challenging application for high-performance computing. Currently, the superscalar architecture dominates todays microprocessor marketplace. As more transistors are integrated onto larger die, however, an on-chip multiprocessor is regarded as a promising alternative to the superscalar microprocessor. This paper examines the behavior of the object recognition on the on-chip multiprocessor, which will be employed in general-purpose parallel machines. To obtain the performance characteristics of the microprocessor, a program-driven simulator and its programming environment were developed. The simulation results showed that the on-chip multiprocessor can exploit thread level parallelisms effectively and offer a promising architecture for the object recognition application.

• 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.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.157-163
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• 2019

The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.50-58
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• 2007

In this paper, we propose a query-based visual attention algorithm for effective object finding of a vision-based mobile robot. This algorithm is developed by extending conventional bottom-up visual attention algorithms. In our proposed algorithm various conspicuity maps are merged to make a saliency map, where weighting values are determined by query-dependent object properties. The saliency map is then used to find possible attentive location of queried object. To show the validities of our proposed algorithm, several objects are employed to compare performances of our proposed algorithm with those of conventional bottom-up approaches. Here, as one of exemplar query-dependent object property, color property is used.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.386-398
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• 2020

We developed an integrative annotation program that can perform data labeling process for deep learning models in object recognition. The program utilizes the basic GUI library of Python and configures crawler functions that allow data collection in real time. Retinanet was used to implement an automatic annotation function. In addition, different data labeling formats for Pascal-VOC, YOLO and Retinanet were generated. Through the experiment of the proposed method, a domestic vehicle image dataset was built, and it is applied to Retinanet and YOLO as the training and test set. The proposed system classified the vehicle model with the accuracy of about 94%.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.200-210
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• 1996

Re-engineering has the potential to improve software productivity and quality y across the entire life cycle. It involves improving the software maintenance process and improving existing systems by applying new technologies and tools to software maintenance. Re-engineering can help us understanding existing systems and discover software components(e.g., design structure, data structure that are common across systems. These common components then can be reused in the development (or redevelopment )of systems, thereby significantly shortening the time and lessening the risk of developing systems. The Object-Oriented paradigm has been known to improve software maintainability. There still exist many problems in recognizing object, attributes and operations that are conceptually integrated and constructing of object class. In this paper, we propose a method that defines a fundamental theories of re-engineering and a concept recognition for object- oriented paradigm. We also describe the re-engineering tool that translates the existing procedure-oriented program into object-oriented system. This tool has a strength to solve the conceptual integrity problem in object-oriented recognition.

• Journal of Korean Elementary Science Education
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• v.30 no.3
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• pp.340-352
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• 2011

The purpose of this study was to analyze effects of teaching materials for elementary science gifted conception about object recognition. Elementary science gifted have misconceptions that they can see in lightness. They can not explain how a shadow is made. This paper reports in-depth investigation on elementary science gifted's understanding of object recognition focusing on process of light. A program is developed to elementary science gifted in the subject matter. The tutorial emphasizing the process of light consists of pre-test, worksheet, and post-test. The Tutorial has 4 steps; darkness and light, light on things, light reached eyes, structure of the eyes. Each steps has 2~4 experiments. Through the tutorial, we expect their misconceptions can be changed into scientific conceptions. For the research and analysis, a questionnaire is posed to 39 elementary science gifted at M Elementary School in D Metropolitan City. The first method of product analysis makes a comparative study of pre-test, post-test score, and hake gain each test. As a result, total score of all student was raised. And hake gain of pre-test(II) is 0.6, hake gain of post-test is 0.68. It is Medium gain. Also, elementary science gifted could understand how we see through the tutorial emphasizing process of light. And their misconceptions can be changed into scientific conceptions.

• Human Ecology Research
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• v.56 no.1
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• pp.99-108
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• 2018

This study develops a scale to measure the practice of consideration and sharing by adolescents. This data as an object of high school students in regards to items generated from the content validity test and preliminary study stage based on the consideration scale, literature review and expert for elementary school students on a 5-point Likert scale. The factor analysis of the collected data using SPSS 20.0 2 indicated the final fators. The three fanal factors designated by the measuring items are: 'practice of consideration and sharing', 'recognition of consideration and sharing', and 'self-recognition'. As a result of analyzing students' individual variables, this study found that family relationship satisfaction and school life satisfaction had positive relationship in self-recognition, recognition of consideration and sharing, practice of consideration and sharing, and total personality score. The measurement tools developed in this study, are expected to act as valid tools to develop a program that can increase the practice of consideration and sharing activities.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.10-17
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• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.