• Title/Summary/Keyword: Object Recognition Technology

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A Study on the Performance Activities of the TQM Implementation in Shipping Industry (해운기업의 TQM활동과 실행성과에 관한 연구)

  • Kim, Dong-Hoon;Shin, Han-Won;Ko, Soo-Bok
    • Journal of Global Scholars of Marketing Science
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    • v.9
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    • pp.129-151
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    • 2002
  • Today, shipping companies have shown the positive volition to the finding of chanced market through the development of new route with the new recognition and enhancement of competitiveness on the quality management in order to cope with the sharply-changing environment of shipping industry. Accordingly, this study is an empirical study which attempts the general and situational approach in order to clarify what TQM source, Activities and performance affect the enterprises and how it is different upon the step of quality management activities in the object of the incidental business related to the oceangoing and costal transportation, and marine and the groups related to the marines, subdividing the area of offering the shipping service.

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Real-time VR Strategy Chess Game using Motion Recognition (VR기반 모션인식을 이용한 실시간 전략 체스 게임)

  • Kim, Young-Kwang;Yoon, Yeo-Song;Oh, Tea-Gyeoung;HwangBo, Yeung-Hwan;Hwang, Jeong-Hee
    • Journal of Digital Contents Society
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    • v.18 no.1
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    • pp.1-7
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    • 2017
  • Virtual reality(VR) is known as immersive multimedia or computer-simulated reality, is a computer technology that replicates an environment, real or imagined, and simulates a user's physical presence and environment to allow for user interaction. Virtual realities artificially create sensory experience including sight, touch, hearing, and smell. Owing to the use of a single device in most VR contents, user have difficulty in manipulating user interface and game object. And also immersion of the game goes down because they can't see the mouse and keyboard in virtual space. In this paper, we design and implement the chess game to easily and accurately control user interface to improve the immersion in game.

A Study on Optimized Mapping Environment for Real-time Spatial Mapping of HoloLens

  • Hwang, Leehwan;Lee, Jaehyun;Hafeez, Jahanzeb;Kang, Jinwook;Lee, Seunghyun;Kwon, Soonchul
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.3
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    • pp.1-8
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    • 2017
  • Recently, the development of the head mounted display (HMD) device has attracted a great deal of attention to the actual contents. Especially, Augmented Reality (AR), which is a mixture of actual information and virtual world information, is focused on. AR HMD is able to interact by arranging virtual objects in real space through spatial recognition using depth camera. In order to naturally mix virtual space with real space, it is necessary to develop a technology for realizing spatial mapping information with high accuracy. The purpose of this paper is to evaluate the optimal configuration of augmented reality application program by realizing accurate spatial mapping information when mapping a real space and an object placement environment using HoloLens. To do this, we changed the spatial mapping information in real space to three levels, which are the number of meshes used in cubic meters to scan step by step. After that, it was compared with the 3D model obtained by changing the actual space and mesh number. Experimental result shows that the higher the number of meshes used in cubic meters, the higher the accuracy between real space and spatial mapping. This paper is expected to be applied to augmented reality application programs that require scanning of highly mapped spatial mapping information.

Generalized Hough Transform using Internal Gradient Information (내부 그레디언트 정보를 이용한 일반화된 허프변환)

  • Chang, Ji Young
    • Journal of Convergence for Information Technology
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    • v.7 no.3
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    • pp.73-81
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    • 2017
  • The generalized Hough transform (GHough) is a useful technique for detecting and locating 2-D model. However, GHough requires a 4-D parameter array and a large amount of time to detect objects of unknown scale and orientation because it enumerates all possible parameter values into a 4-D parameter space. Several n-to-1 mapping algorithms were proposed to reduce the parameter space from 4-D to 2-D. However, these algorithms are very likely to fail due to the random votes cast into the 2-D parameter space. This paper proposes to use internal gradient information in addition to the model boundary points to reduce the number of random votes cast into 2-D parameter space. Experimental result shows that our proposed method can reduce both the number of random votes cast into the parameter space and the execution time effectively.

Performance Improvement of Material Recognition Sensor Using Cubic Spline Interpolation (Spline보간식을 이용한 물체재질인식센서의 성능개선)

  • Park, J.G.;Lim, Y.C.;Cho, K.Y.;Kim, Y.G,;Chang, Y.H.
    • Journal of Sensor Science and Technology
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    • v.1 no.1
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    • pp.43-51
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    • 1992
  • This paper describes a noble robot sensor designed to recognize an unknown material by measuring its thermal conductivity on various ambient temperature. The excellent agreement has been obtained between the measured sensor temperature and the calculated sensor temperature by cubic spline interpolation. The active sensor to measure the thermal conductivity of a gripped object was designed and the software program using C language to discriminate objects made of different materials was developed. The temperature response characteristics of different materials on the same ambient temperature was investigated. The temperatures on three comparing points varied linearly and had parallel relation with one another in accordance with various ambient temperature.

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Improving Matching Performance of SURF Using Color and Relative Position (위치와 색상 정보를 사용한 SURF 정합 성능 향상 기법)

  • Lee, KyungSeung;Kim, Daehoon;Rho, Seungmin;Hwang, Eenjun
    • Journal of Advanced Navigation Technology
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    • v.16 no.2
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    • pp.394-400
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    • 2012
  • SURF is a robust local invariant feature descriptor and has been used in many applications such as object recognition. Even though this algorithm has similar matching accuracy compared to the SIFT, which is another popular feature extraction algorithm, it has advantage in matching time. However, these descriptors do not consider relative location information of extracted interesting points to guarantee rotation invariance. Also, since they use gray image of original color image, they do not use the color information of images, either. In this paper, we propose a method for improving matching performance of SURF descriptor using the color and relative location information of interest points. The location information is built from the angles between the line connecting the centers of interest points and the orientation line constructed for the center of each interest points. For the color information, color histogram is constructed for the region of each interest point. We show the performance of our scheme through experiments.

Classification of Clothing Using Googlenet Deep Learning and IoT based on Artificial Intelligence (인공지능 기반 구글넷 딥러닝과 IoT를 이용한 의류 분류)

  • Noh, Sun-Kuk
    • Smart Media Journal
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    • v.9 no.3
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    • pp.41-45
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    • 2020
  • Recently, artificial intelligence (AI) and the Internet of things (IoT), which are represented by machine learning and deep learning among IT technologies related to the Fourth Industrial Revolution, are applied to our real life in various fields through various researches. In this paper, IoT and AI using object recognition technology are applied to classify clothing. For this purpose, the image dataset was taken using webcam and raspberry pi, and GoogLeNet, a convolutional neural network artificial intelligence network, was applied to transfer the photographed image data. The clothing image dataset was classified into two categories (shirtwaist, trousers): 900 clean images, 900 loss images, and total 1800 images. The classification measurement results showed that the accuracy of the clean clothing image was about 97.78%. In conclusion, the study confirmed the applicability of other objects using artificial intelligence networks on the Internet of Things based platform through the measurement results and the supplementation of more image data in the future.

Development of a Remote Dust Collector Bag Control System using Power Line Communication (전력선 통신을 이용한 원격 집진기 bag 제어 시스템 개발)

  • Kim, Jung-Sook
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.4
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    • pp.91-98
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    • 2010
  • Advances in communications and control technology, the strengthening of the Internet, and the growing recognition of the urgency to reduce the risk and production cost are motivating the development of improvements in the traditional manufacturing industry. In this paper, we developed a remote dust collector bag control system which is a combination of advanced IT and traditional dust collector based on the event. At first, we made the A/D(Analog/Digital) converter using a micro processor because the differential pressure transmission, which is a sensor of the dust collector, produces analog volt data. A/D converter can provide RS-232 communication to connect with Power Line Communication(PLC) modem. And, n-bytes message format was defined for the efficient dust collector bag information transmission from a dust collector to a user. Also, we designed the data types to model the dust collector and the dust collector bag, and they were logically modeled using XML and object-oriented modeling method. In addition to that, we implemented the system for showing the dust collector bag exchange time exactly to users at real-time using various visual user interfaces.

An intelligent video security system for the tracking of multiple moving objects (복수의 동체 추적을 위한 지능형 영상보안 시스템)

  • Kim, Byung-Chul
    • Journal of Digital Convergence
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    • v.11 no.10
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    • pp.359-366
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    • 2013
  • Due to the development and market expansion of image analysis and recognition technology, video security such as CCTV cameras and digital storage devices, are required for real-time monitoring systems and intelligent video security systems. This includes the development of more advanced technologies. A rotatable PTZ camera, in a CCTV camera system, has a zoom function so you can acquire a precise picture. However it can cause blind spots, and can not monitor two or more moving objects at the same time. This study concerns, the intelligent tracking of multiple moving objects, CCTV systems, and methods of video surveillance. An intelligent video surveillance system is proposed. It can accurately shoot broad areas and track multiple objects at the same time, much more effectively than using one fixed camera for an entire area or two or more PTZ cameras.

On Optimizing Dissimilarity-Based Classifier Using Multi-level Fusion Strategies (다단계 퓨전기법을 이용한 비유사도 기반 식별기의 최적화)

  • Kim, Sang-Woon;Duin, Robert P. W.
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.5
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    • pp.15-24
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    • 2008
  • For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.