• Title/Summary/Keyword: Corner detector

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Ship Design Visualization System base on Augmented Reality (증강현실 기반의 선박설계 시각화 시스템)

  • Park, Mi-Jeong;Yoo, Seung-Hyeok;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.249-251
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    • 2012
  • Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

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Panoramic Image Composition Algorithm through Scaling and Rotation Invariant Features (크기 및 회전 불변 특징점을 이용한 파노라마 영상 합성 알고리즘)

  • Kwon, Ki-Won;Lee, Hae-Yeoun;Oh, Duk-Hwan
    • The KIPS Transactions:PartB
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    • v.17B no.5
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    • pp.333-344
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    • 2010
  • This paper addresses the way to compose paronamic images from images taken the same objects. With the spread of digital camera, the panoramic image has been studied to generate with its interest. In this paper, we propose a panoramic image generation method using scaling and rotation invariant features. First, feature points are extracted from input images and matched with a RANSAC algorithm. Then, after the perspective model is estimated, the input image is registered with this model. Since the SURF feature extraction algorithm is adapted, the proposed method is robust against geometric distortions such as scaling and rotation. Also, the improvement of computational cost is achieved. In the experiment, the SURF feature in the proposed method is compared with features from Harris corner detector or the SIFT algorithm. The proposed method is tested by generating panoramic images using $640{\times}480$ images. Results show that it takes 0.4 second in average for computation and is more efficient than other schemes.

The Study of a Correlation between Heat Release and Smoke Production by Using Oxygen Consumption Calorimeter Up to 10 MW Facility (10MW급 까지의 산소소모율법 칼로리미터를 활용한 열방출률과 연기발생률의 상관성에 관한 연구)

  • Ryu, Sang-Hoon;Yoo, Yong-Ho;Rie, Dong-Ho
    • Fire Science and Engineering
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    • v.24 no.3
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    • pp.58-65
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    • 2010
  • The fire accidents having recently occurred are getting more and more larger and causing lots of damage in terms of property loss and casualties increase, so there is in need of technical fire safety development like comprehensive prevention solution in order to effectively prevent. Especially, the needing of new paradigm for advanced fire safe technology is gathering strength in high-rise modern building construction. Therefore, we want to find out on this paper what is a correlation between heat release rate measurement and smoke release volume by three parts of oxygen consumption calorimeter in bench scale calorimeter (cone calorimeter/ISO 5660/Avg.500Kw), Medium scale calorimeter (Room corner tester, Single burning Item/ISO 9750, EN 13823/Avg.3MW), and large scale calorimeter (Industry calorimeter/Avg. 10MW). Thus, Smoke detective of new paradigm devised by making use of a correlation between heat release and smoke production is to help reduce loss property and casualties. Ultimately, based on this theory, a new concept of fire alarm and evacuation system will be developed and expected to apply to a skyscraper.

Shape Recognition of 3-D Protein Molecules Using Feature and Pocket Points (포켓과 특징 점을 이용한 3차원 단백질 분자 형상인식)

  • Lee, Hang-Chan
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.75-81
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    • 2011
  • Protein molecules are combined with another ones which have similar shapes at pocket positions. The pocket positions can be good references to describe the shapes of protein molecules. Harris corner detector is commonly used to detect feature points of 2 or 3D objects. Feature points can be found on the pocket areas and the points which have high derivatives. Generally speaking, the densities of feature points are relatively high at pocket areas because the shapes of pockets are concave. The pocket areas can be decided by the subdivision of voxel cubes which include feature points. The Euclidean distances between feature points and the central coordinate of the decided pocket area are calculated and sorted. The graph of sorted distances describes the shape of a protein molecule and the distribution of feature points. Therefore, it can be used to classify protein molecules by their shapes. Even though the shapes of protein molecules have been distorted with noises, they can be recognized with the accuracy more than 95 %. The accurate shape recognition provides the information to predict the binding properties of protein molecules.

A Study on the Integrated Control and Safety Management System for 9% Ni Steel LNG Storage Tank (9% 니켈강재식 LNG 저장탱크용 통합제어안전관리시스템에 관한 연구)

  • Kim, Chung-Kyun
    • Journal of the Korean Institute of Gas
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    • v.14 no.5
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    • pp.13-18
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    • 2010
  • This paper presents the development of an integrated control and safety management system for 9% nickel steel LNG storage tank. The new system added the measuring equipment of pressure, displacement and force compared to the conventional measurement and control system. The measured data has simultaneously been processed by integrating and analyzing with new control equipments and safety management systems. The integrated control and safety management system, which may increase a safety and efficiency of a super-large full containment LNG storage tank, added additional pressure gauges and new displacement/force sensors at the outer side wall and a welding zone of a stiffener and top girder of an inner tank, and the inner side wall of a corner protection tank. The displacement and force sensors may provide failure clues of 9% nickel steel structures such as an inner tank and a corner protection, and a LNG leakage from the inner tank. The conventional leak sensor may not provide proper information on 9% nickel steel tank fracture even though LNG is leaked until the leak detector, which is placed at the insulation area between an inner tank and a corner protection tank, sends a warning signal. Thus, the new integrated control and safety management system is to collect and analyze the temperature, pressure, displacement, force, and LNG density, which are related to the tank system safety and leakage control from the inner tank. The digital data are also measured from control systems such as displacement and force of 9% nickel steel tank safety, LNG level and density, cool-down process, leakage, and pressure controls.

Development of a Cost-Effective Tele-Robot System Delivering Speaker's Affirmative and Negative Intentions (화자의 긍정·부정 의도를 전달하는 실용적 텔레프레즌스 로봇 시스템의 개발)

  • Jin, Yong-Kyu;You, Su-Jeong;Cho, Hye-Kyung
    • The Journal of Korea Robotics Society
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    • v.10 no.3
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    • pp.171-177
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    • 2015
  • A telerobot offers a more engaging and enjoyable interaction with people at a distance by communicating via audio, video, expressive gestures, body pose and proxemics. To provide its potential benefits at a reasonable cost, this paper presents a telepresence robot system for video communication which can deliver speaker's head motion through its display stanchion. Head gestures such as nodding and head-shaking can give crucial information during conversation. We also can assume a speaker's eye-gaze, which is known as one of the key non-verbal signals for interaction, from his/her head pose. In order to develop an efficient head tracking method, a 3D cylinder-like head model is employed and the Harris corner detector is combined with the Lucas-Kanade optical flow that is known to be suitable for extracting 3D motion information of the model. Especially, a skin color-based face detection algorithm is proposed to achieve robust performance upon variant directions while maintaining reasonable computational cost. The performance of the proposed head tracking algorithm is verified through the experiments using BU's standard data sets. A design of robot platform is also described as well as the design of supporting systems such as video transmission and robot control interfaces.

Feature Based Multi-Resolution Registration of Blurred Images for Image Mosaic

  • Fang, Xianyong;Luo, Bin;He, Biao;Wu, Hao
    • International Journal of CAD/CAM
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    • v.9 no.1
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    • pp.37-46
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    • 2010
  • Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration, but not suitable for the naturally blurred images existing in the real image mosaic process. In this paper, we attempt to resolve this problem and propose a method for a distortion-free stitching of naturally blurred images for image mosaic. It adopts a multi-resolution and robust feature based inter-layer mosaic together. In each layer, Harris corner detector is chosen to effectively detect features and RANSAC is used to find reliable matches for further calibration as well as an initial homography as the initial motion of next layer. Simplex and subspace trust region methods are used consequently to estimate the stable focal length and rotation matrix through the transformation property of feature matches. In order to stitch multiple images together, an iterative registration strategy is also adopted to estimate the focal length of each image. Experimental results demonstrate the performance of the proposed method.

Fast Shape Matching Algorithm Based on the Improved Douglas-Peucker Algorithm (개량 Douglas-Peucker 알고리즘 기반 고속 Shape Matching 알고리즘)

  • Sim, Myoung-Sup;Kwak, Ju-Hyun;Lee, Chang-Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.10
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    • pp.497-502
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    • 2016
  • Shape Contexts Recognition(SCR) is a technology recognizing shapes such as figures and objects, greatly supporting technologies such as character recognition, motion recognition, facial recognition, and situational recognition. However, generally SCR makes histograms for all contours and maps the extracted contours one to one to compare Shape A and B, which leads to slow progress speed. Thus, this paper has made simple yet more effective algorithm with optimized contour, finding the outlines according to shape figures and using the improved Douglas-Peucker algorithm and Harris corner detector. With this improved method, progress speed is recognized as faster.

A Practical Solution toward SLAM in Indoor environment Based on Visual Objects and Robust Sonar Features (가정환경을 위한 실용적인 SLAM 기법 개발 : 비전 센서와 초음파 센서의 통합)

  • Ahn, Sung-Hwan;Choi, Jin-Woo;Choi, Min-Yong;Chung, Wan-Kyun
    • The Journal of Korea Robotics Society
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    • v.1 no.1
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    • pp.25-35
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    • 2006
  • Improving practicality of SLAM requires various sensors to be fused effectively in order to cope with uncertainty induced from both environment and sensors. In this case, combining sonar and vision sensors possesses numerous advantages of economical efficiency and complementary cooperation. Especially, it can remedy false data association and divergence problem of sonar sensors, and overcome low frequency SLAM update caused by computational burden and weakness in illumination changes of vision sensors. In this paper, we propose a SLAM method to join sonar sensors and stereo camera together. It consists of two schemes, extracting robust point and line features from sonar data and recognizing planar visual objects using multi-scale Harris corner detector and its SIFT descriptor from pre-constructed object database. And fusing sonar features and visual objects through EKF-SLAM can give correct data association via object recognition and high frequency update via sonar features. As a result, it can increase robustness and accuracy of SLAM in indoor environment. The performance of the proposed algorithm was verified by experiments in home -like environment.

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Medical Image Automatic Annotation Using Multi-class SVM and Annotation Code Array (다중 클래스 SVM과 주석 코드 배열을 이용한 의료 영상 자동 주석 생성)

  • Park, Ki-Hee;Ko, Byoung-Chul;Nam, Jae-Yeal
    • The KIPS Transactions:PartB
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    • v.16B no.4
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    • pp.281-288
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    • 2009
  • This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.