• Title/Summary/Keyword: 코너 검출

검색결과 90건 처리시간 0.03초

Defect detection of vacuum insulation panel using image analysis based on corner feature detection (코너 특정점 기반의 영상분석을 활용한 진공단열재 결함 검출)

  • Kim, Beom-Soo;Yang, Jeonghyeon;Kim, Yeonwon
    • Journal of the Korean institute of surface engineering
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    • 제55권6호
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    • pp.398-402
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    • 2022
  • Vacuum Insulation Panel (VIP) is an high energy efficient insulation system that facilitate slim but high insulation performance, based on based on a porous core material evacuated and encapsulated in a multi-barrier envelope. Although VIP has been on the market for decades now, it wasn't until recently that efforts have been initiated to propose a standard on aging testing. One of the issues regarding VIP is its durability and aging due to pressure and moisture dependent increase of the initial low thermal conductivity with time. It is hard to visually determine at an early stage. Recently, a method of analyzing the damage on the a material surface by applying image processing technology has been widely used. These techniques provide fast and accurate data with a non-destructive way. In this study, the surface VIP images were analyzed using the Harris corner detection algorithm. As a result, 171,333 corner points in the normal packaging were detected, whereas 32,895 of the defective packaging, which were less than the normal packaging. were detected. These results are considered to provide meaningful information for the determination of VIP condition.

Dry Magnetic Particle Inspection of Ingot Cast Billets (강편 빌레트의 건식 자분 탐상)

  • Kim, Goo-Hwa;Lim, Zhong-Soo;Lee, Eui-Wan
    • Journal of the Korean Society for Nondestructive Testing
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    • 제16권3호
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    • pp.162-173
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    • 1996
  • Dry magnetic particle inspection(MPI) was performed to detect the surface defects of steel ingot cast billets. Magnetic properties of several materials were characterized by the measurement of the B-H hysteresis curve. The inspection results were evaluated in terms of the magnetizing current, temperature, and the amount of magnetic particles applied to billets. Magnetic flux leakage near the defect site of interest was measured and compared with the results of calculation by the finite element method in the case of direct magnetizing current. Direct and alternating magnetizing currents for materials were deduced by the comparison of the inspections. Results of the magnetic particle inspection by direct magnetizing current were compared with those of finite element method calculations, which were verified by measuring magnetic leakage flux above the surface and the surface defects of the material. For square rods, due to the geometrical effect, the magnetic flux density at the edges along the length of the rods was about 30% of that at the center of rod face for a sufficiently large direct magnetizing current, while it was about 70% for an alternating magnetizing current. Thus, an alternating magnetizing current generates rather uniform magnetic flux density over the rods, except for the region on the face across about 10 mm from the edge. The attraction of the magnetic particle by the magnetic leakage field was nearly independent of the surface temperature of the billets up to $150^{\circ}C$. However, the temperature should have been limited below $60^{\circ}C$ for an effective fixing of gathered magnetic particles to the billet surface using methylene chloride. We also found that the amount of applied magnetic particles tremendously affected the detection capability.

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Ship Design Visualization System base on Augmented Reality (증강현실 기반의 선박설계 시각화 시스템)

  • Park, Mi-Jeong;Yoo, Seung-Hyeok;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국정보통신학회 2012년도 춘계학술대회
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    • pp.249-251
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    • 2012
  • Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

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Medical Image Automatic Annotation Using Multi-class SVM and Annotation Code Array (다중 클래스 SVM과 주석 코드 배열을 이용한 의료 영상 자동 주석 생성)

  • Park, Ki-Hee;Ko, Byoung-Chul;Nam, Jae-Yeal
    • The KIPS Transactions:PartB
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    • 제16B권4호
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    • pp.281-288
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    • 2009
  • This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

Localization of a Tracked Robot Based on Fuzzy Fusion of Wheel Odometry and Visual Odometry in Indoor and Outdoor Environments (실내외 환경에서 휠 오도메트리와 비주얼 오도메트리 정보의 퍼지 융합에 기반한 궤도로봇의 위치추정)

  • Ham, Hyeong-Ha;Hong, Sung-Ho;Song, Jae-Bok;Baek, Joo-Hyun;Ryu, Jae-Kwan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • 제36권6호
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    • pp.629-635
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    • 2012
  • Tracked robots usually have poor localization performance because of slippage of their tracks. This study proposes a new localization method for tracked robots that uses fuzzy fusion of stereo-camera-based visual odometry and encoder-based wheel odometry. Visual odometry can be inaccurate when an insufficient number of visual features are available, while the encoder is prone to accumulating errors when large slips occur. To combine these two methods, the weight of each method was controlled by a fuzzy decision depending on the surrounding environment. The experimental results show that the proposed scheme improved the localization performance of a tracked robot.

A Voronoi Distance Based Searching Technique for Fast Image Registration (고속 영상 정합을 위한 보르노이 거리 기반 분할 검색 기법)

  • Bae Ki-Tae;Chong Min-Yeong;Lee Chil-Woo
    • The KIPS Transactions:PartB
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    • 제12B권3호
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    • pp.265-272
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    • 2005
  • In this paper, we propose a technique which is speedily searching for correspondent points of two images using Voronoi-Distance, as an image registration method for feature based image mosaics. It extracts feature points in two images by the SUSAN corner detector, and then create not only the Voronoi Surface which has distance information among the feature points in the base image using a priority based Voronoi distance algorithm but also select the model area which has the maximum variance value of coordinates of the feature points in the model image. We propose a method for searching for the correspondent points in the Voronoi surface of the base image overlapped with the model area by use of the partitive search algorithm using queues. The feature of the method is that we can rapidly search for the correspondent points between adjacent images using the new Voronoi distance algorithm which has $O(width{\times}height{\times}logN)$ time complexity and the the partitive search algerian using queues which reduces the search range by a fourth at a time.

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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    • 제11권5호
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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.

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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    • 제29권1호
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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.

Detection of Illegal U-turn Vehicles by Optical Flow Analysis (옵티컬 플로우 분석을 통한 불법 유턴 차량 검지)

  • Song, Chang-Ho;Lee, Jaesung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제39C권10호
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    • pp.948-956
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    • 2014
  • Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

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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    • 제21권1호
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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.