• Title/Summary/Keyword: Hough space

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Iris Localization using the Pupil Center Point based on Deep Learning in RGB Images (RGB 영상에서 딥러닝 기반 동공 중심점을 이용한 홍채 검출)

  • Lee, Tae-Gyun;Yoo, Jang-Hee
    • Journal of Software Assessment and Valuation
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    • v.16 no.2
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    • pp.135-142
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    • 2020
  • In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

Detection of Lane Marking Candidates by Using Scale-space (스케일-공간을 이용한 차선 마킹 후보 검출)

  • Yoo, Hyeon-Joong
    • Transactions of the Korean Society of Automotive Engineers
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    • v.21 no.4
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    • pp.43-53
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    • 2013
  • Lane marking detection based on a mono camera sensor provides a low cost solution to both ITS (intelligent transportation systems) and DAS (driver assistant systems). A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue. Traditional approaches are mostly based on statistics or Hough transforms. However, the former approaches usually include many irrelevant detection areas, and the latter are not practical because actual lanes are not usually suitable for the approximation with linear or polynomial equations. In this paper, we focus on increasing the reliability of detection by reducing the detection of irrelevant areas while improving the detection of actual lane marking areas, which is usually a tradeoff for most conventional approaches. We use scale-space for that. Through experiments with real images obtained from various environments, we could achieve a significant improvement over traditional approaches.

Aerial scene matching using linear features (선형특징을 사용한 항공영상의 정합)

  • 정재훈;박영태
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.689-692
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    • 1998
  • Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching is presented. A set of andidate parameters are hypthesized by mapping the angular difference and a new distance measure to the hough space and by detecting maximally consistent points. The proposed method is shown to be much faster than the conventinal one where the relaxation process is repeated until convergence, while providing robust matching performance, without a priori information on the geometrical transformation parameters.

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Linear Feature Detection of Rectangular Object Area using Edge Tracing-based Algorithm (에지 트레이싱 기법을 이용한 사각형 물체의 선형 특징점 검출)

  • 오중원;한희일
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2092-2095
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    • 2003
  • In this paper, we propose an algorithm to extract rectangular object area such 3s Data Matrix two-dimensional barcode using edge tracing-based linear feature detection. Hough transform is usually employed to detect lines of edge map. However, it requires parametric image space, and does not find the location of end points of the detected lines. Our algorithm detects end points of the detected lines using edge tracing and extracts object area using its shape information.

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A Study on the Automation of Interior Orientation and Relative Orientation (내부표정과 상호표정의 자동화에 관한 연구)

  • Jeong, Soo;Park, Choung-Hwan;Yun, Kong-Hyun;Yeu, Bock-Mo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.17 no.2
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    • pp.105-116
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    • 1999
  • Owing to the rapid development of computer system and the introduction of image processing technique, recent photogrammetric studies have been concentrated on the automation of photogrammetric orientation work that have been carried out by skilled professionals in analog and/or analytical pbotogrammetric field. To automate the whole photogrammetric work, the automation of the orientation processes including interior, relative and absolute orientation should be preceded. This study aims to automate interior orientation and relative orientation process. For this purpose, we applied Hough transform to interior orientation process and object space matching technique to relative orientation process. As the result of this study, we can present a method to automate interior and relative orientation process that has been semi-automatically operated in most commercial digital photogrammetric workstations currently available.

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Label Restoration Using Biquadratic Transformation

  • Le, Huy Phat;Nguyen, Toan Dinh;Lee, Guee-Sang
    • International Journal of Contents
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    • v.6 no.1
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    • pp.6-11
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    • 2010
  • Recently, there has been research to use portable digital camera to recognize objects in natural scene images, including labels or marks on a cylindrical surface. In many cases, text or logo in a label can be distorted by a structural movement of the object on which the label resides. Since the distortion in the label can degrade the performance of object recognition, the label should be rectified or restored from deformations. In this paper, a new method for label detection and restoration in digital images is presented. In the detection phase, the Hough transform is employed to detect two vertical boundaries of the label, and a horizontal edge profile is analyzed to detect upper-side and lower-side boundaries of the label. Then, the biquadratic transformation is used to restore the rectangular shape of the label. The proposed algorithm performs restoration of 3D objects in a 2D space, and it requires neither an auxiliary hardware such as 3D camera to construct 3D models nor a multi-camera to capture objects in different views. Experimental results demonstrate the effectiveness of the proposed method.

A Study on the Development of Guide Line Measurement System in the Driving Condition (주행상태에서의 가이드라인 계측 시스템 개발에 관한 연구)

  • Kim, Young-Bok
    • Journal of Power System Engineering
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    • v.15 no.5
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    • pp.91-96
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    • 2011
  • The handling ability of containers at the terminal strongly depends on the performance of the cargo handling system such as RTGC(Rubber Tired Gantry Crane) and RMGC(Rail Mounted Gantry Crane). This paper introduces a guide line measurement system on the operating condition, in which two camera are installed to detect the guide line. Because the line tracking is the basic technique for control system design of RTGC, it is necessary to develop a useful and reliable measurement system. If the displacement and angle of the RTGC relative to a guide line as the trajectory to follow is obtained, the position of RTGC is automatically calculated. Therefore, in this paper, a camera-based measurement system is introduced. The proposed measurement system is robust against light fluctuation and cracks of the guide line. This system consists of two camera and a PC which are installed at the lower side of the RTGC. Two edges of the guide line are detected from an input image taken by the cameras in the moving state, and these positions are determined in a Hough parameter space by using the Hough transformation method. From the experimental results, the accuracy and usefulness of the proposed system is evaluated by comparing other instruments.

Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

Detection and Recognition of Traffic Lights for Unmanned Autonomous Driving (무인 자율주행을 위한 신호등의 검출과 인식)

  • Kim, Jang-Won
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.6
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    • pp.751-756
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    • 2018
  • This research extracted traffic light from input video, recognized colors of traffic light, and suggested traffic light color recognizing algorithm applicable to manless autonomous vehicle or ITS by distinguishing signs. To extract traffic light, suggested algorithm extracted the outline with CEA(Canny Edge Algorithm), and applied HCT(Hough Circle Transform) to recognize colors of traffic light and improve the accuracy. The suggested method was applied to the video of stream acquired on the road. As a result, excellent rate of traffic light recognition was confirmed. Especially, ROI including traffic light in input video was distinguished and computing time could be reduced. In even area similar to traffic light, circle was not extracted or V value is low in HSV space, so it's failed in candidate area. So, accuracy of recognition rate could be improved.

A Study on Finding the Rail Space in Elevators Using Matched Filter

  • Song, Myong-Lyol
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.57-65
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    • 2019
  • In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.