• Title/Summary/Keyword: polar histogram

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Obstacle avoidance using Vector Field Histogram in simulation (Vector Field Histogram를 이용한 장애물 회피 시뮬레이션)

  • 정현룡;김영배
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.1076-1079
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    • 2003
  • The vector field histogram(VFH) uses a two-dimensional Cartesian histogram grid as a world model. The VFH method subsequently employs a two-stage data-reduction process in order to compute the desired control commands for the vehicle. In the first stage the histogram grid is reduced to a one dimensional polar histogram that is constructed around the robot's momentary location. Each sector in the polar histogram contains a value representing the polar obstacle density in that direction. In the second stage, the algorithm selects the most suitable sector from among all polar histogram sectors with a low polar obstacle density, and the steering of the robot is aligned with that direction. We applied this algorithm to our simulation program and tested..

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Obstacle a voidance using VFH (Vector Field Histogram) in four legged robot (VFH(Vector Field Histogram)을 이용한 4족 로봇의 장애물 회피)

  • Jung, Hyun-Ryong;Kim, Young-Bae
    • Proceedings of the KIEE Conference
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    • 2003.11b
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    • pp.23-26
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    • 2003
  • The vector field histogram(VFH) uses a two-dimensional Cartesian histogram grid as a world model. The VFH method subsequently employs a two-stage data-reduction process in order to compute the desired control commands for the vehicle. In the first stage the histogram grid is reduced to a one dimensional polar histogram that is constructed around the robot's momentary location. Each sector in the polar histogram contains a value representing the polar obstacle density in that direction. In the second stage, the algorithm selects the most suitable sector from among all polar histogram sectors with a low polar obstacle density, and the steering of the robot is aligned with that direction. We applied this algorithm to our four-legged robot.

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맵-빌딩을 이용한 사족 로봇의 장애물 회피

  • 고환규;유창범;김영배
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.05a
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    • pp.277-277
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    • 2004
  • 로봇의 실시간 장애물 회피 방법은 연구되어 왔고 실행되어 왔다. 이러한 방법을 vector field histogram(VFH)라 하며 이러한 방법은 알려져 있지 않는 장애물의 발견과 장애물과의 충돌을 피하는 동시에 목표점으로의 로봇의 이동을 위한 알고리즘이다. The vector field histogram(VFH)방법은 world model로 이차원 Cartesian histogram grid를 이용하였다. VFH 방법은 Vehicle을 원하는 데로 컨트롤하기 위한 과정으로 두 단계 데이터 줄이는 과정이다. Histogram grid 의 첫 번째 단계는 로봇의 순간위치를 구성하기 위한 일 차원 polar histogram에 포함된 각 섹터의 값은 polar obstacle density(POD)로 방향을 표시한다.(중략)

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Signatures Verification by Using Nonlinear Quantization Histogram Based on Polar Coordinate of Multidimensional Adjacent Pixel Intensity Difference (다차원 인접화소 간 명암차의 극좌표 기반 비선형 양자화 히스토그램에 의한 서명인식)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.5
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    • pp.375-382
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    • 2016
  • In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

Comparison of Image Duplication Detection Using the Polar Coordinates System and Histogram of Oriented Gradients Methods

  • Gunadi, Kartika;Adipranata, Rudy;Suryajaya, Ivan
    • Journal of information and communication convergence engineering
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    • v.17 no.1
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    • pp.67-73
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    • 2019
  • In the current era of digital technology, and with the help of existing software, digital photo manipulation is becoming easier and faster. One example of this is the development of powerful image processing software that makes it easy for a digital image to be manipulated and edited. It is therefore very important to protect and maintain public trust in digital images. Several methods have been developed to detect image manipulation. In this paper, we compare two methods for detecting image duplication due to copy-move actions, namely the polar coordinate system and the histogram of oriented gradients methods. The former is a method based on the transfer of a Cartesian image to a polar form, making it easy to tell whether there are objects that have undergone a copy/move in an image, while the latter is a method for retrieving information related to the distribution, which uses a target in the local area as a tool to represent the shape of the target. We compare the accuracy, speed and memory usage of these two methods.

VFH+ based Obstacle Avoidance using Monocular Vision of Unmanned Surface Vehicle (무인수상선의 단일 카메라를 이용한 VFH+ 기반 장애물 회피 기법)

  • Kim, Taejin;Choi, Jinwoo;Lee, Yeongjun;Choi, Hyun-Taek
    • Journal of Ocean Engineering and Technology
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    • v.30 no.5
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    • pp.426-430
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    • 2016
  • Recently, many unmanned surface vehicles (USVs) have been developed and researched for various fields such as the military, environment, and robotics. In order to perform purpose specific tasks, common autonomous navigation technologies are needed. Obstacle avoidance is important for safe autonomous navigation. This paper describes a vector field histogram+ (VFH+) based obstacle avoidance method that uses the monocular vision of an unmanned surface vehicle. After creating a polar histogram using VFH+, an open space without the histogram is selected in the moving direction. Instead of distance sensor data, monocular vision data are used for make the polar histogram, which includes obstacle information. An object on the water is recognized as an obstacle because this method is for USV. The results of a simulation with sea images showed that we can verify a change in the moving direction according to the position of objects.

Performance Enhancement of an Obstacle Avoidance Algorithm using a Network Delay Compensationfor a Network-based Autonomous Mobile Robot (네트워크 기반 자율이동 로봇을 위한 시간지연 보상을 통한 장애물 회피 알고리즘의 성능 개선)

  • Kim, Joo-Min;Kim, Jin-Woo;Kim, Dae-Won
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1898-1899
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    • 2011
  • In this paper, we propose an obstacle avoidance algorithm for a network-based autonomous mobile robot. The obstacle avoidance algorithm is based on the VFH (Vector Field Histogram) algorithm and delay-compensative methods with the VFH algorithm are proposed for the network-based robot that is a unified system composed of distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the compensated readings of the sensors are used for building the polar histogram of the VFH algorithm. Secondly, a sensory fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of the readings of an odometry sensor and the delay of the readings of the environmental sensors. The performance enhancements of the proposed obstacle avoidance algorithm from the viewpoint of efficient path generation and accurate goal positioning are also shown in this paper through some simulation experiments by the Marilou Robotics Studio Simulator.

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Development of an Obstacle Avoidance Algorithm for a Network-based Autonomous Mobile Robot (네트워크 기반 자율이동로봇을 위한 장애물 회피 알고리즘 개발)

  • Kim Hongryeol;Kim Dae Won;Kim Hong-Seok;Sohn SooKyung
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.5
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    • pp.291-299
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    • 2005
  • An obstacle avoidance algorithm for a network-based autonomous mobile robot is proposed in this paper. The obstacle avoidance algorithm is based on the VFH(Vector Field Histogram) algorithm and two delay compensation methods with the VFH algorithm are proposed for a network-based robot with distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the environmental sensor information is compensated by prospection with acquired environmental sensor information, measured network delays, and the kinematic model of the robot. The compensated environmental sensor information is used for building polar histogram with the VFH algorithm. Secondly, a sensor fusion algorithm for localization of the robot is proposed to compensate the delay of odometry sensor information and the delay of environmental sensor information. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal positioning is shown here.

Obstacle Avoidance Navigation Using Distance Profile Histogram (거리 형태 히스토그램을 이용한 이동로보트의 장애물 회피 주행)

  • 김현태;노흥식;조영완;박민용
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.12
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    • pp.1-12
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    • 1996
  • A new local path planning algorithm using DPH (distance profile histogram) is suggested in this paper. The proposed method makes a grid type world map using distance values from multiple ultrasonic sensors and genrates local points through which the mobile robot can avoid obstcles safely. The DPH (distance profile historgram) represents geometrical arrangement of obstacles around the robot in the local polar coordinate system which is assumed to be atached to the robot. To control robot's navigation, a three-layered control structure is adopted. The proposed local path planning algorithm is placed on the top level. And a point-to-point translation controller takes the middle level. The bottom level consists of a velcoity servo and sonar driver modules which take charge of driving physical hardwares. The validity of the propsoed method is demonstated through several experiments.

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The Application of BP and RBF Neural Network Methods on Vehicle Detection in Aerial Imagery

  • Choi, Jae-Young;Jang, Hyoung-Jong;Yang, Young-Kyu
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.473-481
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    • 2008
  • This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.