• Title/Summary/Keyword: Range Feature

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Stereo Matching Method using Directional Feature Vector (방향성 특징벡터를 이용한 스테레오 정합 기법)

  • Moon, Chang-Gi;Jeon, Jong-Hyun;Ye, Chul-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.1
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    • pp.52-57
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    • 2007
  • In this paper we proposed multi-directional matching windows combined by multi-dimensional feature vector matching, which uses not only intensity values but also multiple feature values, such as variance, first and second derivative of pixels. Multi-dimensional feature vector matching has the advantage of compensating the drawbacks of area-based stereo matching using one feature value, such as intensity. We define matching cost of a pixel by the minimum value among eight multi-dimensional feature vector distances of the pixels expanded in eight directions having the interval of 45 degrees. As best stereo matches, we determine the two points with the minimum matching cost within the disparity range. In the experiment we used aerial imagery and IKONOS satellite imagery and obtained more accurate matching results than that of conventional matching method.

Surface Segmentation and Feature Description using the Signature Technique (Signature 기법을 이용한 면의 특징 표현 및 분할 기법)

  • 이보형;한헌수
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.12
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    • pp.90-97
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    • 1997
  • This paper presents a new algorithm for surface segmentation and feature description. The algorithm extracts the signature of an edge image based on the signature technqique[12] in the first stage. If there exists a range in the angle axis where more than two signatures form a closed curve, we can conclude there is a surface inside the range. Using this feature of the signature, surfaces can be segmented. The surface features such as number of vertices, number of edges, and type of surfaces can also be extracted by finding the signatures of individual surfaces. This algorithm has distinguished advantages: it can easily recover the lost part occuring in the edge iage using the curve fitting method and it can extract surface features even when surfaces are rotated in 3-D space.

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Multi-camera based Images through Feature Points Algorithm for HDR Panorama

  • Yeong, Jung-Ho
    • International journal of advanced smart convergence
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    • v.4 no.2
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    • pp.6-13
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    • 2015
  • With the spread of various kinds of cameras such as digital cameras and DSLR and a growing interest in high-definition and high-resolution images, a method that synthesizes multiple images is being studied among various methods. High Dynamic Range (HDR) images store light exposure with even wider range of number than normal digital images. Therefore, it can store the intensity of light inherent in specific scenes expressed by light sources in real life quite accurately. This study suggests feature points synthesis algorithm to improve the performance of HDR panorama recognition method (algorithm) at recognition and coordination level through classifying the feature points for image recognition using more than one multi frames.

ISAR Cross-Range Scaling for a Maneuvering Target (기동표적에 대한 ISAR Cross-Range Scaling)

  • Kang, Byung-Soo;Bae, Ji-Hoon;Kim, Kyung-Tae;Yang, Eun-Jung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.10
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    • pp.1062-1068
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    • 2014
  • In this paper, a novel approach estimating target's rotation velocity(RV) is proposed for inverse synthetic aperture radar(ISAR) cross-range scaling(CRS). Scale invariant feature transform(SIFT) is applied to two sequently generated ISAR images for extracting non-fluctuating scatterers. Considering the fact that the distance between target's rotation center(RC) and SIFT features is same, we can set a criterion for estimating RV. Then, the criterion is optimized through the proposed method based on particle swarm optimization(PSO) combined with exhaustive search method. Simulation results show that the proposed algorithm can precisely estimate RV of a scenario based maneuvering target without RC information. With the use of the estimated RV, ISAR image can be correctly re-scaled along the cross-range direction.

Optimal Placement of Sensor Nodes with 2.4GHz Wireless Channel Characteristics (2.4GHz 무선 채널 특성을 가진 센서 노드의 최적 배치)

  • Jung, Kyung-Kwon;Eom, Ki-Hwan
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.1
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    • pp.41-48
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    • 2007
  • In this paper, we propose an optimal placement of sensor nodes with 2.4GHz wireless channel characteristics. The proposed method determines optimal transmission range based on log-normal path loss model, and optimal number of sensor nodes calculating the density of sensor nodes. For the lossless data transmission, we search the optimal locations with self-organizing feature maps(SOM) using transmission range, and number of sensor nodes. We demonstrate that optimal transmission range is 20m, and optimal number of sensor nodes is 8. We performed simulations on the searching for optimal locations and confirmed the link condition of sensor nodes.

Development of the Computer Vision based Continuous 3-D Feature Extraction System via Laser Structured Lighting (레이저 구조광을 이용한 3차원 컴퓨터 시각 형상정보 연속 측정 시스템 개발)

  • Im, D. H.;Hwang, H.
    • Journal of Biosystems Engineering
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    • v.24 no.2
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    • pp.159-166
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    • 1999
  • A system to extract continuously the real 3-D geometric fearture information from 2-D image of an object, which is fed randomly via conveyor has been developed. Two sets of structured laser lightings were utilized. And the laser structured light projection image was acquired using the camera from the signal of the photo-sensor mounted on the conveyor. Camera coordinate calibration matrix was obtained, which transforms 2-D image coordinate information into 3-D world space coordinate using known 6 points. The maximum error after calibration showed 1.5 mm within the height range of 103mm. The correlation equation between the shift amount of the laser light and the height was generated. Height information estimated after correlation showed the maximum error of 0.4mm within the height range of 103mm. An interactive 3-D geometric feature extracting software was developed using Microsoft Visual C++ 4.0 under Windows system environment. Extracted 3-D geometric feature information was reconstructed into 3-D surface using MATLAB.

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Side Scan Sonar based Pose-graph SLAM (사이드 스캔 소나 기반 Pose-graph SLAM)

  • Gwon, Dae-Hyeon;Kim, Joowan;Kim, Moon Hwan;Park, Ho Gyu;Kim, Tae Yeong;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.12 no.4
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    • pp.385-394
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    • 2017
  • Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

Range Data Acquistion and Shape Feature Extraction (거리영상의 획득 및 형상특징 추출)

  • Cho, Dong-Uk;Kim, Ji-Yeong;Lee, Boo-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.11 no.1
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    • pp.42-51
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    • 1992
  • This paper proposes an acquisition and the representation method of the 3-dimensional information. The proposed range finder system can reduce the computation time by only calculating the ${\triangle}R$ of each pixel compared to the existing methods. We also propose a shape feature extraction method by considering the sign change of the acquired range data. Finally, the effectiveness of this system is demonstrated by several experiments.

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Energy Feature Normalization for Robust Speech Recognition in Noisy Environments

  • Lee, Yoon-Jae;Ko, Han-Seok
    • Speech Sciences
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    • v.13 no.1
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    • pp.129-139
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    • 2006
  • In this paper, we propose two effective energy feature normalization methods for robust speech recognition in noisy environments. In the first method, we estimate the noise energy and remove it from the noisy speech energy. In the second method, we propose a modified algorithm for the Log-energy Dynamic Range Normalization (ERN) method. In the ERN method, the log energy of the training data in a clean environment is transformed into the log energy in noisy environments. If the minimum log energy of the test data is outside of a pre-defined range, the log energy of the test data is also transformed. Since the ERN method has several weaknesses, we propose a modified transform scheme designed to reduce the residual mismatch that it produces. In the evaluation conducted on the Aurora2.0 database, we obtained a significant performance improvement.

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Fractal behavior identification for monitoring data of dam safety

  • Su, Huaizhi;Wen, Zhiping;Wang, Feng
    • Structural Engineering and Mechanics
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    • v.57 no.3
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    • pp.529-541
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    • 2016
  • Under the interaction between dam body, dam foundation and external environment, the dam structural behavior presents the time-varying nonlinear characteristics. According to the prototypical observations, the correct identification on above nonlinear characteristics is very important for dam safety control. It is difficult to implement the description, analysis and diagnosis for dam structural behavior by use of any linear method. Based on the rescaled range analysis approach, the algorithm is proposed to identify and extract the fractal feature on observed dam structural behavior. The displacement behavior of one actual dam is taken as an example. The fractal long-range correlation for observed displacement behavior is analyzed and revealed. The feasibility and validity of the proposed method is verified. It is indicated that the mechanism evidence can be provided for the prediction and diagnosis of dam structural behavior by using the fractal identification method. The proposed approach has a high potential for other similar applications.