• Title/Summary/Keyword: Image binarization

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A study on the Automatic Detection of the Welding Dimension Defect of Steel Construct using Digital Image Processing (디지털 화상처리에 의한 강.구조물의 용접부 치수 결함 검출의 자동화에 관한 연구)

  • Kim, Jae-Yeol;You, Sin;Park, Ki-Hyung
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.8 no.3
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    • pp.92-99
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    • 1999
  • The inspection unit which is developed and used in this study, is processed the shape data from the CCD camera to seek welding bite section shape, and then calculated as a real dimension from measuring the value of each inspection item. The reason of measuring with the real in this study is came out from the image method which used for a long time, which is extricated the characteristic as the dimension of pixel by recognize pixel. The measurement method of the section shape is that we decide the thresholding value after we drew the histogram to binarizate the object. After that, we make flat the object to get rid of the noise and measure the shape of welded part through the boundarization of the object. The shape measurement is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual dimension of the standard specimen and the dimension of image, to measure the ratio between the actual product and the camera image. The inspection algorithm which estimates the quality of welded product is developed and also, the software GUI(Graphic User Interface) which processes the automatic test function of the inspection system is developed. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

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Extracting gall bladders from ultrasound images

  • Kim, Hyoung-Seop;Ishikawa, Seiji;Kato, Kiyoshi;Tsukuda, Masaaki;Matsuoka, Jun-nosuke
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.248-251
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    • 1995
  • Nowadays, the internal images of a human body can be easily provided by the ultrasound imaging, the X-ray CT, or the MRI device, among which the ultrasound imaging device has good resolution for soft tissues of a human body compared with the other devices. Furthermore, the use of ultrasound imaging devices will increase in future especially in the obstetrics, territory, since it does not give harm to the human body. Although several techniques have been investigated until now in order to extract organs from ultrasound images, very few of them have achieved satisfactory results because of low contrast and high noise nature of images. This paper proposes a technique for automatic extraction of the gall bladder area from ultrasound images. The proposed technique first extracts a small reliable area of a gall bladder from an ultrasound image employing smoothing, binarization, expanding and shrinking, and labeling, and then expands the area referring to the binarized version of the original image. The technique is examined its performance by real ultrasound images of a gall bladder and satisfactory results are obtained. Some problems to be solved are discussed finally.

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Image Processing Based Time-Frequency Domain Reflectometry for Estimating the Fault Location Close to the Applied Signal Point (케이블 내 근접 결함 추정을 위한 영상 처리 기반의 시간 주파수 영역 반사파 계측법)

  • Jeong, Jong Min;Lee, Chun Ku;Yoon, Tae Sung;Park, Jin Bae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.12
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    • pp.1683-1689
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    • 2014
  • In this paper, we propose an image processing based time-frequency domain reflectometry(TFDR) in order to estimate the fault location of a cable. The Wigner-Ville distribution is used for analysis in both the time domain and the frequency domain when the conventional TFDR estimates the fault location in a cable. However, the Winger-Ville distribution is a bi-linear function, and hence the cross-term is occurred. The conventional TFDR cannot estimate the accurate fault location due to the cross-term in case the fault location is close to the position where the reference signal is applied to the cable. The proposed method can reduce the cross-term effectively using binarization and morphological image processing, and can estimate the fault location more accurately using the template matching based cross correlation compared to the conventional TFDR. To prove the performance of the proposed method, the actual experiments are carried out in some cases.

Light 3D Modeling with mobile equipment (모바일 카메라를 이용한 경량 3D 모델링)

  • Ju, Seunghwan;Seo, Heesuk;Han, Sunghyu
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.4
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    • pp.107-114
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    • 2016
  • Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

Tumor Detection Algorithm by using Mammogram Image Processing (맘모그램 영상처리를 이용한 종양검출 알고리즘)

  • Song, Kyohyuk;Chon, Minhee;Joo, Wonjong;Kim, Gibom
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.3_1spc
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    • pp.496-503
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    • 2013
  • Recently, the death rate owing to breast cancers has been increasing, and the occurrence age for breast cancers is lowering every year. Mammography is known to be a reliable detection method for breast cancers and works by detecting texture changes, calcifications, and other potential symptoms. In this research on breast cancer detection, candidate objects were detected by using image processing on mammograms, and feature analysis was used to classify candidate objects as benign tumors and malignant tumors. To find candidate objects, image pre-processing and binarization using multiple thresholds, and the grouping of micro-calcifications were used. More than 50 shape features and intensity features were used in the classification. The performance of the detection algorithm by using Euclidian distance method for benign tumors was 93%, and the classification error rate was approximately 2%.

The Study of Hanji and Washi Fiber Orientation using Image analysis (Image analysis에 의한 한지와 화지의 섬유 배향성 연구)

  • Han, Yoon-Hee;Enomae, Toshiharu;Isogai, Akira
    • Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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    • 2006.11a
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    • pp.89-96
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    • 2006
  • To estimate the manufacturing district and generation of ancient paper as a cultural property, fiber orientation is one of the criteria. Image analysis using fast Fourier transform with suitable modifications was demonstrated to be an effective means to determine angle and intensity of fiber orientation as a nondestructive method. Binarization process of microscopic images of paper surface and precise calculation for average Fourier coefficients as an angular distribution by linear interpolation were newly introduced in the procedures to improve the accuracy. This analysis method was applied to digital optical micrographs of paper surfaces. Korea and Japanese traditional hand making papers were well distinguished. Korea and Japanese papers made in the traditional ways showed its own characteristic orientation behavior in accordance with the motion of a bamboo wire.

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A Knowledge-Based System for Address Block Location on Korean Envelope Images (우리나라 우편 봉투 영상에서의 주소 영역 추추을 위한 지식 기반 시스템)

  • 김기철;이성환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.8
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    • pp.137-147
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    • 1994
  • In this paper,we propose a knowledge-based system for locating Destination Address Block(DAB) by analyzing the structure of Korean envelope images. In the proposed system the preprocessing steps such as adaptive binarization connected component extraction and deskewing are carried out first for the effective structure analysis of the envelope image. Then DAB containing address name and zipcode parts of the input envelope image is extracted by an iterative procedure based on the knowledge acquired from the statistical feature analysis of the various envelope images. Most of the system for slocating address blocks on envelopes have extracted DAB by segmenting an envelope image into several candidate blocks followed by selecting one among the candidate blocks. Because it is very difficult to segment a Korean envelope image into several blocks due to the specific writing habits that the addresses on the envelope are written in close proximity to each other the proposed iterative procedure determines DAB by splitting or merging the connected components and verifies the determined DAB without segmentation and selection. Experiments with a great number of the live envelopes provided from Seoul Mail Center in Koorea were carried out. The results reveal that the proposed system is very effective for address block location on Korean envelopes.

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Character Detection in Complex Scene Image using Harris Corner Detector (해리스 코너 검출기를 이용한 배경 영상에서의 문자 검출)

  • Kim, Min-ha;Kim, Mi-kyung;Cha, Eui-young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.97-100
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    • 2013
  • In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

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Incorporating Recognition in Catfish Counting Algorithm Using Artificial Neural Network and Geometry

  • Aliyu, Ibrahim;Gana, Kolo Jonathan;Musa, Aibinu Abiodun;Adegboye, Mutiu Adesina;Lim, Chang Gyoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.12
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    • pp.4866-4888
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    • 2020
  • One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

The Development of Visual Inspection for Length Measurement of Injection Product Using Vision System (Vision System을 이용한 사출제품의 길이 측정용 시각검사 System 개발)

  • J.Y. Kim;B.S. Oh;S. You
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.11
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    • pp.126-134
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    • 1997
  • In this study, We made visual inspection system using Vision Board. It is consist of an illuminator (a fluorescent lamp), image input device (CCD (Charge-Coupled Device) camera), image processing system(Vision Board(FARAMVB-02)), image output device (video monitor, printer), and a measuring instrument(TELMN1000). Length measurement by visual inspection system make use of 100mm guage block(instead of calculating distance between a camera and a object). It measured horizontal and vertical length factor from 400mm to 650mm by increasing 50mm. In this place, measured horizontal and vertical length factor made use of length measure- ment of a injection. A measuring instrument used to ompare a measured length of a injection visual inspection system with it. In conclusion, length measurement of a injection compared a measuring instrument with visual inspecion system using length factor of 100mm gauge block. We find that maximum error of length is 0.55mm when it compar with the measuring value of two devices(FARAMVB-02, TELMN1000). Program of visual inspection system is made up Borland C++3.1.

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