• Title/Summary/Keyword: Corner detection

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Measurement of Fine 6-DOF Displacement using a 3-facet Mirror (삼면반사체를 이용한 6자유도 미소 변위 측정)

  • 박원식;조형석;변용규;박노열
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.50-50
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    • 2000
  • In this paper, a new measuring system is :proposed which can measure the fine 6-DOF displacement of rigid bodies. Its measurement principle is based on detection of laser beam reflected from a specially fabricated mirror that looks like a triangular pyramid having an equilateral cross-sectional shape. The mirror has three lateral reflective surfaces inclined 45$^{\circ}$ to its bottom surface. We call this mirror 3-facet mirror. The 3-facet mirror is mounted on the object whose 6-DOF displacement is to be measured. The measurement is operated by a laser-based optical system composed of a 3-facet mirror, a laser source, three position-sensitive detectors(PSD). In the sensor system, three PSDs are located at three corner points of a triangular formation, which is an equilateral triangular formation tying parallel to the reference plane. The sensitive areas of three PSDs are oriented toward the center point of the triangular formation. The object whose 6-DOF displacement is to be measured is situated at the center with the 3-facet mirror on its top surface. A laser beam is emitted from the laser source located at the upright position and vertically incident on the top of the 3-fatcet mirror. Since each reflective facet faces toward each PSD, the laser beam is reflected at the 3-facet mirror and splits into three sub-beams, each of which is reflected from the three facets and finally arrives at three PSDs, respectively. Since each PSD is a 2-dimensional sensor, we can acquire the information on the 6-DOF displacement of the 3-facet mirror. From this principle, we can get 6-DOF displacement of any object simply by mounting the 3-facet mirror on the object. In this paper, we model the relationship between the 6-DOF displacement of the object and the outputs of three PSDs. And, a series of simulations are performed to demonstrate the effectiveness of the proposed method. The simulation results show that the proposed sensing system can be an effective means of obtaining 3-dimensional position and orientation of arbitrary objects.

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A Low Cost 3D Skin Wrinkle Reconstruction System Based on Stereo Semi-Dense Matching (반 밀집 정합에 기반한 저가형 3차원 주름 데이터 복원)

  • Zhang, Qian;WhangBo, Taeg-Keun
    • Journal of Internet Computing and Services
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    • v.10 no.4
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    • pp.25-33
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    • 2009
  • In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

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Wine Label Recognition System using Image Similarity (이미지 유사도를 이용한 와인라벨 인식 시스템)

  • Jung, Jeong-Mun;Yang, Hyung-Jeong;Kim, Soo-Hyung;Lee, Guee-Sang;Kim, Sun-Hee
    • The Journal of the Korea Contents Association
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    • v.11 no.5
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    • pp.125-137
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    • 2011
  • Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

Real-Time Feature Point Matching Using Local Descriptor Derived by Zernike Moments (저니키 모멘트 기반 지역 서술자를 이용한 실시간 특징점 정합)

  • Hwang, Sun-Kyoo;Kim, Whoi-Yul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.4
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    • pp.116-123
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    • 2009
  • Feature point matching, which is finding the corresponding points from two images with different viewpoint, has been used in various vision-based applications and the demand for the real-time operation of the matching is increasing these days. This paper presents a real-time feature point matching method by using a local descriptor derived by Zernike moments. From an input image, we find a set of feature points by using an existing fast corner detection algorithm and compute a local descriptor derived by Zernike moments at each feature point. The local descriptor based on Zernike moments represents the properties of the image patch around the feature points efficiently and is robust to rotation and illumination changes. In order to speed up the computation of Zernike moments, we compute the Zernike basis functions with fixed size in advance and store them in lookup tables. The initial matching results are acquired by an Approximate Nearest Neighbor (ANN) method and false matchings are eliminated by a RANSAC algorithm. In the experiments we confirmed that the proposed method matches the feature points in images with various transformations in real-time and outperforms existing methods.

Electroglottographic Measurements of Glottal Function in Voice according to Gender and Age

  • Ko, Do-Heung
    • Phonetics and Speech Sciences
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    • v.3 no.1
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    • pp.97-102
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    • 2011
  • Electroglottography (EGG) is a common method for providing non-invasive measurements of glottal activity. EGG has been used in vocal pathology as a clinical or research tool to measure vocal fold contact. This paper presents the results of pitch, jitter, and closed quotient (CQ) measurements in electroglottographic signals of young (mean = 22.7 years) and elderly (mean = 74.3 years) male and female subjects. The sustained corner vowels /i/, /a/, and /u/ were measured at around 70 dB SPL since the most notable among EGG variables is the phonation intensity, which showed positive correlation with closed phase. The aim of this paper was to measure EGG data according to age and gender. In CQ, there was a significant difference between young and elderly female subjects while there was no significant difference between young and elderly male subjects. The mean value for young males was higher than that for elderly males while the mean value for young females was lower than that for elderly females. Thus, it can be said that in mean values, increased CQ was related to decreased age for females, while CQ decreased for males as the speaker's age decreased. Although the laryngeal degeneration due to increased age seems to occur to a lesser extent in females, the significant increase of CQ in elderly female voices could not be explained in terms of age-related physiological changes. In standard deviation of pitch and jitter, the mean values for young and elderly males were higher than that for young and elderly females. That is, male subjects showed higher in mean values of voice variables than female subjects. This result could be considered as a sign of vocal instability in males. It was suggested that these results may provide powerful insights into the control and regulation of normal phonation and into the detection and characterization of pathology.

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3D Model Reconstruction Algorithm Using a Focus Measure Based on Higher Order Statistics (고차 통계 초점 척도를 이용한 3D 모델 복원 알고리즘)

  • Lee, Joo-Hyun;Yoon, Hyeon-Ju;Han, Kyu-Phil
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.11-18
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    • 2013
  • This paper presents a SFF(shape from focus) algorithm using a new focus measure based on higher order statistics for the exact depth estimation. Since conventional SFF-based 3D depth reconstruction algorithms used SML(sum of modified Laplacian) as the focus measure, their performance is strongly depended on the image characteristics. These are efficient only for the rich texture and well focused images. Therefore, this paper adopts a new focus measure using HOS(higher order statistics), in order to extract the focus value for relatively poor texture and focused images. The initial best focus area map is generated by the measure. Thereafter, the area refinement, thinning, and corner detection methods are successively applied for the extraction of the locally best focus points. Finally, a 3D model from the carefully selected points is reconstructed by Delaunay triangulation.

Implementation of ROS-Based Intelligent Unmanned Delivery Robot System (ROS 기반 지능형 무인 배송 로봇 시스템의 구현)

  • Seong-Jin Kong;Won-Chang Lee
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.610-616
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    • 2023
  • In this paper, we implement an unmanned delivery robot system with Robot Operating System(ROS)-based mobile manipulator, and introduce the technologies employed for the system implementation. The robot consists of a mobile robot capable of autonomous navigation inside the building using an elevator and a Selective Compliance Assembly Robot Arm(SCARA)-Type manipulator equipped with a vacuum pump. The robot can determines the position and orientation for picking up a package through image segmentation and corner detection using the camera on the manipulator. The proposed system has a user interface implemented to check the delivery status and determine the real-time location of the robot through a web server linked to the application and ROS, and recognizes the shipment and address at the delivery station through You Only Look Once(YOLO) and Optical Character Recognition(OCR). The effectiveness of the system is validated through delivery experiments conducted within a 4-story building.

Computer Vision-Based Measurement Method for Wire Harness Defect Classification

  • Yun Jung Hong;Geon Lee;Jiyoung Woo
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.77-84
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    • 2024
  • In this paper, we propose a method for accurately and rapidly detecting defects in wire harnesses by utilizing computer vision to calculate six crucial measurement values: the length of crimped terminals, the dimensions (width) of terminal ends, and the width of crimped sections (wire and core portions). We employ Harris corner detection to locate object positions from two types of data. Additionally, we generate reference points for extracting measurement values by utilizing features specific to each measurement area and exploiting the contrast in shading between the background and objects, thus reflecting the slope of each sample. Subsequently, we introduce a method using the Euclidean distance and correction coefficients to predict values, allowing for the prediction of measurements regardless of changes in the wire's position. We achieve high accuracy for each measurement type, 99.1%, 98.7%, 92.6%, 92.5%, 99.9%, and 99.7%, achieving outstanding overall average accuracy of 97% across all measurements. This inspection method not only addresses the limitations of conventional visual inspections but also yields excellent results with a small amount of data. Moreover, relying solely on image processing, it is expected to be more cost-effective and applicable with less data compared to deep learning methods.

An Inquiry Over Rayleigh's Pioneering Experiments for the Detection of Shadow, Reflection, Interference, and Diffraction of Sound (소리의 그늘, 반사, 간섭, 회절의 검출을 위한 레일리의 선구적 실험에 대한 연구)

  • Ku, Ja-Hyon
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2
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    • pp.55-60
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    • 2007
  • The shadow, reflection, interference, and diffraction are proper phenomena concerning sound that is a kind of wave. By the late nineteenth century, similar optical phenomena had been detected already but these phenomena concerning sound had not been convincingly detected. It was Rayleigh who succeeded in detecting those phenomena without any reasonable doubt by the virtue of his original instruments and smart experimental settings. Rayleigh could detect the sound shadow by using the corner of a building and erase the shadow by some reflectors. And he constructed some apparatus similar to Young's interference apparatus famous in optics to detect the sonic interference. Furthermore, he first succeeded in illustrating the acoustical effectiveness of Poisson's disk by which optical diffraction had already been well known, and tested the effect of diffraction by spherical obstacles to ascertain that the result coincided with his theory.

Robust Semi-auto Calibration Method for Various Cameras and Illumination Changes (다양한 카메라와 조명의 변화에 강건한 반자동 카메라 캘리브레이션 방법)

  • Shin, Dong-Won;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.21 no.1
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    • pp.36-42
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    • 2016
  • Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.