• 제목/요약/키워드: Feature Point Detection

검색결과 249건 처리시간 0.026초

Automatic detection of the optimal ejecting direction based on a discrete Gauss map

  • Inui, Masatomo;Kamei, Hidekazu;Umezu, Nobuyuki
    • Journal of Computational Design and Engineering
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    • 제1권1호
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    • pp.48-54
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    • 2014
  • In this paper, the authors propose a system for assisting mold designers of plastic parts. With a CAD model of a part, the system automatically determines the optimal ejecting direction of the part with minimum undercuts. Since plastic parts are generally very thin, many rib features are placed on the inner side of the part to give sufficient structural strength. Our system extracts the rib features from the CAD model of the part, and determines the possible ejecting directions based on the geometric properties of the features. The system then selects the optimal direction with minimum undercuts. Possible ejecting directions are represented as discrete points on a Gauss map. Our new point distribution method for the Gauss map is based on the concept of the architectural geodesic dome. A hierarchical structure is also introduced in the point distribution, with a higher level "rough" Gauss map with rather sparse point distribution and another lower level "fine" Gauss map with much denser point distribution. A system is implemented and computational experiments are performed. Our system requires less than 10 seconds to determine the optimal ejecting direction of a CAD model with more than 1 million polygons.

포인트 클라우드 기반 선체 구조 변형 탐지 알고리즘 적용 연구 (Application of Point Cloud Based Hull Structure Deformation Detection Algorithm)

  • 송상호;이갑헌;한기민;장화섭
    • 대한조선학회논문집
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    • 제59권4호
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    • pp.235-242
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    • 2022
  • As ship condition inspection technology has been developed, research on collecting, analyzing, and diagnosing condition information has become active. In ships, related research has been conducted, such as analyzing, detecting, and classifying major hull failures such as cracks and corrosion using 2D and 3D data information. However, for geometric deformation such as indents and bulges, 2D data has limitations in detection, so 3D data is needed to utilize spatial feature information. In this study, we aim to detect hull structural deformation positions. It builds a specimen based on actual hull structure deformation and acquires a point cloud from a model scanned with a 3D scanner. In the obtained point cloud, deformation(outliers) is found with a combination of RANSAC algorithms that find the best matching model in the Octree data structure and dataset.

Interest Point Detection Using Hough Transform and Invariant Patch Feature for Image Retrieval

  • ;안영은;박종안
    • 한국ITS학회 논문지
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    • 제8권1호
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    • pp.127-135
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    • 2009
  • This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.

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셀룰라 비선형 네트워크를 이용한 특징점 궤적 상에서 Optical Flow 검출 (Detection of Optical Flows on the Trajectories of Feature Points Using the Cellular Nonlinear Neural Networks)

  • 손혼락;김형숙
    • 전자공학회논문지CI
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    • 제37권6호
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    • pp.10-21
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    • 2000
  • 거리 변환(Distance Transform)을 수행할 수 있는 셀룰라 비선형 네트워크 구조와 특징 점들의 제적 상에서 거리 변환을 이용한 optical flow 검출 방법을 제안하였다. 움직이는 물체의 추적이나 카메라의 움직임 파악 같은 응용 분야에서는 수가 적더라도 정확하고 확실한 optical flow가 더 중요하다. 본 연구는 특징점들의 이동 궤적 상에서 거리 변환 기법을 이용하여 거리 변환 필드(Distance Transform Field)를 생성시키고 거리 변환 필드상에서 궤적의 움직인 거리 값과 방향을 추출함으로써 optical flow를 구하는 방법이다. 이 방법은 영상 정보를 거리 정보로 변환하여 사용하게 되므로 잡음의 영향을 적게 받으며 필요한 연산들이 아날로그 회로에 의해 처리되므로 처리 속도가 빠르고, 지역적 처리 특성을 갖기 때문에 하드웨어 구현이 용이하다는 특징이 있다. 또한, 본 연구에서는 제안한 알고리즘의 핵심부분을 하드웨어로 구현하기 위해 셀룰라 비선형 네트워크(Celluar Nonlinear Neural Network)구조를 제안하였다. 제안한 구조와 알고리즘을 검증하기 위해 다양한 영상과 환경에 대한 시뮬레이션을 수행하여 결과를 제시하였다.

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3차원 측정 데이터와 영상 데이터를 이용한 특징 형상 검출 (Feature Detection using Measured 3D Data and Image Data)

  • 김한솔;정건화;장민호;김준호
    • 한국정밀공학회지
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    • 제30권6호
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    • pp.601-606
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    • 2013
  • 3D scanning is a technique to measure the 3D shape information of the object. Shape information obtained by 3D scanning is expressed either as point cloud or as polygon mesh type data that can be widely used in various areas such as reverse engineering and quality inspection. 3D scanning should be performed as accurate as possible since the scanned data is highly required to detect the features on an object in order to scan the shape of the object more precisely. In this study, we propose the method on finding the location of feature more accurately, based on the extended Biplane SNAKE with global optimization. In each iteration, we project the feature lines obtained by the extended Biplane SNAKE into each image plane and move the feature lines to the features on each image. We have applied this approach to real models to verify the proposed optimization algorithm.

RANSAC을 이용한 실외 도로 환경의 소실점 예측 방법 (The Method of Vanishing Point Estimation in Natural Environment using RANSAC)

  • 원선희;주성일;최형일
    • 한국컴퓨터정보학회논문지
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    • 제18권9호
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    • pp.53-62
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    • 2013
  • 본 논문에서는 입력된 자연영상으로부터 도로 영역을 검출하기 위한 소실점 자동 예측 방법을 제안한다. 제안하는 방법에서는 도로 환경에서 안정적으로 소실점을 검출하기 위해 영상의 주방향성을 분석하여 영상 특징성분들이 집중되는 곳을 소실점으로 예측한다. 이를 위해 첫번째 단계에서는, 영상을 일정크기의 서브블록으로 분할하고 분할된 서브블록 내에서 임의의 에지 샘플을 선택하고 RANSAC을 적용하여 직선 모델을 예측함으로서 각 서브블록의 주방향성을 분석한다. 모든 블록에 대하여 주방향성을 검출한 후, 두 번째 단계에서 임의의 직선 샘플을 선택하고 RANSAC을 적용하여 교점 모델을 예측함으로서 각 직선들로 인한 교점 모델의 비용값을 측정하고 가장 높은 비용값의 교점 모델에 의한 평균점으로 소실점을 예측한다. 마지막으로 성능 검증을 위해 다양한 상황에 따른 정량적, 정성적 분석을 통해 제안하는 소실점 검출 알고리즘의 타당성과 효율성을 입증한다.

전동휠체어 주행안전을 위한 3차원 깊이카메라 기반 장애물검출 (3D Depth Camera-based Obstacle Detection in the Active Safety System of an Electric Wheelchair)

  • 서준호;김창원
    • 제어로봇시스템학회논문지
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    • 제22권7호
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    • pp.552-556
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    • 2016
  • Obstacle detection is a key feature in the safe driving control of electric wheelchairs. The suggested obstacle detection algorithm was designed to provide obstacle avoidance direction and detect the existence of cliffs. By means of this information, the wheelchair can determine where to steer and whether to stop or go. A 3D depth camera (Microsoft KINECT) is used to scan the 3D point data of the scene, extract information on obstacles, and produce a steering direction for obstacle avoidance. To be specific, ground detection is applied to extract the obstacle candidates from the scanned data and the candidates are projected onto a 2D map. The 2D map provides discretized information of the extracted obstacles to decide on the avoidance direction (left or right) of the wheelchair. As an additional function, cliff detection is developed. By defining the "cliffband," the ratio of the predefined band area and the detected area within the band area, the cliff detection algorithm can decide if a cliff is in front of the wheelchair. Vehicle tests were carried out by applying the algorithm to the electric wheelchair. Additionally, detailed functions of obstacle detection, such as providing avoidance direction and detecting the existence of cliffs, were demonstrated.

지능형 홈을 위한 사용자 식별 및 출입 감지 시스템 (User Identification and Entrance/Exit Detection System for Smart Home)

  • 이선우
    • 제어로봇시스템학회논문지
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    • 제14권3호
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    • pp.248-253
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    • 2008
  • This paper presents a sensing system for smart home which can detect an location transition events such as entrance/exit of a member and identify the user in a group at the same time. The proposed system is compose of two sub-systems; a wireless sensor network system and a database server system. The wireless sensing system is designed as a star network where each of sensing modules with ultrasonic sensors and a Bluetooth RF module connect to a central receiver called Bluetooth access point. We propose a method to discriminate a user by measuring the height of the user. The differences in the height of users is a key feature for discrimination. At the same time, the each sensing module can recognize whether the user goes into or out a room by using two ultrasonic sensors. The server subsystem is a sort of data logging system which read the detected event from the access point and then write it into a database system. The database system could provide the location transition information to wide range of context-aware applications for smart home easily and conveniently. We evaluate the developed method with experiments for three subjects in a family with the installation of the developed system into a real house.

맥파전달속도 계산을 위한 특징점 검출 알고리즘 개발 (Development of a Characteristic Point Detection Algorithm for the Calculation of Pulse Wave Velocity)

  • 이낙범;임재중
    • 전기학회논문지
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    • 제57권5호
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    • pp.902-907
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    • 2008
  • Shape of the pulse waveform is affected by the visco-elasticity characteristics of the arterial wall and the reflection waves generated at the bifurcations of arterial branches. This study was designed to improve the accuracy for the extraction of pulse wave features, then proved the superiority of the developed algorithm by clinical evaluation. Upstroke point of the pulse wave was used as an extraction feature since it is minimally affected by the waveform variation. R-peak of the ECG was used as a reference to decide the minimum level, then intersection of the least squares of regression line was used as an upstroke point. Developed algorithm was compared with the existing minimum value detection algorithm and tangent-intersection algorithm using data obtained from 102 subjects. Developed algorithm showed the least standard deviation of $0.29{\sim}0.44\;m/s$ compared with that of the existing algorithms, $0.91{\sim}3.66\;m/s$. Moreover, the rate of standard deviation of more than 1.00m/s for the PWV values reduced with the range of $29.0{\sim}42.4%$, which proved the superiority of the newly developed algorithm.

이산 HM을 이용한 실시간 음성인식 다이얼링 시스템 개발 (Development of a Read-time Voice Dialing System Using Discrete Hidden Markov Models)

  • 이세웅;최승호;이미숙;김홍국;오광철;김기철;이황수
    • The Journal of the Acoustical Society of Korea
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    • 제13권1E호
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    • pp.89-95
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    • 1994
  • 본 논문에서는 화자독립으로 100단어를 인식할 수 있는 실시간 음성인식 다이얼링 시스템의 개발에 대하여 기술하였다. 이 시스템에서 음성인식 알고리즘은 전화선 인터페이스를 갖춘 DSP 보드상에 구현되었으며, IBM PC AT/486 상에서 작동된다. DSP 보드에서는 단어의 시작점이 검출된 후에 특징추출, 벡터양자화 그리고 끝점검출 과정이 실시간으로 10 msec의 프레임 구간마다 수행된다. 또한, 본 시스템에서는 인식시간과 기억용량을 줄이기 위해 VQ 코드북의 크기와 끝점검출 과정을 최적화하였다. 본 실시간 음성인식 다이얼링 시스템은 데모 시스템으로 구현되어 대전엑스포‘93에서 한국이동통신의 MOBILAB 내에 전시되었다.

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