• Title/Summary/Keyword: 균열 영역 인식

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Cracks Information Analysis of Concrete Slab Surface (콘크리트 슬래브 표면의 균열 정보 분석)

  • No, Dae-Kyeung;Kim, Kwang-Beak
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.399-405
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    • 2008
  • 콘크리트 슬래브 표면의 영상처리 목적은 구조물의 균열발생을 최소화하고 발생한 균열에 대해서 지속적인 기록 관리로 균열의 진행 상태를 분석하여 보수시기 및 보수공법 적용의 합리적 운영체계를 수립하고자 하는 것이다. 일반적으로 콘크리트에서의 균열은 육안으로 분간할 수 있을 정도로 큰 반면 프리스트레스트 콘크리트의 균열은 기기를 사용하여야 측정, 분별할 수 있다. 본 논문에서는 균열의 명함도와 인접한 표면의 명함도 차이를 이용하여 균열과 잡음을 분리한다. 그리고 균열과 잡음 영역에서 형태학적인 정보를 이용하여 잡음 영역만을 제거한다. 잡음 영역이 제거된 균열 영역에서도 미세한 잡음이 존재하므로 균열 영역을 평활화를 한 후, 미세 잡음을 하나의 객체로 인식하여 제거하고 끊어진 영역의 균열을 미디언 필터를 이용하여 균열을 연결한다. 그리고 제안된 방법으로 추출된 균열을 원본 영상에 적용하여 최종적으로 균열만을 검출한다. 검출된 균열에서 균열의 특정부분을 선택하고 선택되어진 균열 영상을 대상으로 균열의 길이, 방향, 폭을 순차적으로 분석한다. 실제 균열 영상을 대상으로 실험한 결과, 균열이 비교적 정확히 검출되었고 균열 검사기가 한번에 측정할 때에 비해 비교적 빠르고 적은 노력으로 측정할 수 있는 것을 확인하였다.

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Extraction and Recognition of Concrete Slab Surface Cracks using ART2-based RBF Network (ART2 기반 RBF 네트워크를 이용한 콘크리트 슬래브 표면의 균열 추출 및 인식)

  • Kim, Kwang-Baek
    • Journal of Korea Multimedia Society
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    • v.10 no.8
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    • pp.1068-1077
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    • 2007
  • This paper proposes a method that extracts characteristics of cracks such as length, thickness and direction from a concrete slab surface image with image processing techniques. These techniques extract the cracks from the concrete surface image in variable conditions including bad image conditions) using the ART2-based RBF network to recognize the dominant directions -45 degree, 45 degree, horizontal and vertical) of the extracted cracks from the automatically calculated specifications like the lengths, directions and widths of the cracks. Our proposed extraction algorithms and analysis of the concrete cracks used a Robert operation to emphasize the cracks, and a Multiple operation to increase the difference in brightness between the cracks and background. After these treatments, the cracks can be extracted from the image by using an iterated binarization technique. Noise reduction techniques are used three separate times on this binarized image, and the specifications of the cracks are extracted form this noiseless image. The dominant directions can be recognized by using the ART2-based RBF network. In this method, the ART2 is used between the input layer and the middle layer to learn, and the Delta learning method is used between the middle layer and the output layer. The experiments using real concrete images showed that the cracks were effectively extracted, and the Proposed ART2-based RBF network effectively recognized the directions of the extracted cracks.

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Automatic Fracture Detection in CT Scan Images of Rocks Using Modified Faster R-CNN Deep-Learning Algorithm with Rotated Bounding Box (회전 경계박스 기능의 변형 FASTER R-CNN 딥러닝 알고리즘을 이용한 암석 CT 영상 내 자동 균열 탐지)

  • Pham, Chuyen;Zhuang, Li;Yeom, Sun;Shin, Hyu-Soung
    • Tunnel and Underground Space
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    • v.31 no.5
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    • pp.374-384
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    • 2021
  • In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

Adversarial learning for underground structure concrete crack detection based on semi­supervised semantic segmentation (지하구조물 콘크리트 균열 탐지를 위한 semi-supervised 의미론적 분할 기반의 적대적 학습 기법 연구)

  • Shim, Seungbo;Choi, Sang-Il;Kong, Suk-Min;Lee, Seong-Won
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.22 no.5
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    • pp.515-528
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    • 2020
  • Underground concrete structures are usually designed to be used for decades, but in recent years, many of them are nearing their original life expectancy. As a result, it is necessary to promptly inspect and repair the structure, since it can cause lost of fundamental functions and bring unexpected problems. Therefore, personnel-based inspections and repairs have been underway for maintenance of underground structures, but nowadays, objective inspection technologies have been actively developed through the fusion of deep learning and image process. In particular, various researches have been conducted on developing a concrete crack detection algorithm based on supervised learning. Most of these studies requires a large amount of image data, especially, label images. In order to secure those images, it takes a lot of time and labor in reality. To resolve this problem, we introduce a method to increase the accuracy of crack area detection, improved by 0.25% on average by applying adversarial learning in this paper. The adversarial learning consists of a segmentation neural network and a discriminator neural network, and it is an algorithm that improves recognition performance by generating a virtual label image in a competitive structure. In this study, an efficient deep neural network learning method was proposed using this method, and it is expected to be used for accurate crack detection in the future.

Development of Automatic Crack Detection using the Gabor Filter for Concrete Structures of Railway Tracks (가버 필터를 사용한 철도 콘크리트 궤도 도상의 자동 균열 감지 개발)

  • Na, Yong-Hyoun;Park, Mi-Yun;Park, Ji-Soo;Park, Sung-Baek;Kwon, Se-Gon
    • Journal of the Society of Disaster Information
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    • v.14 no.4
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    • pp.458-465
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    • 2018
  • Purpose: Concrete track that affects on railway safety can detect cracks using image processing technique. However, since a condition of concrete track and surface noisy are obstructed to detect cracks, there is a need for a way to remove them effectively. Method: In this study, we proposed an image processing to detect cracks effectively for Korean railway and verified its performance through experiment. We developed image acquisition system for capture a railway concrete track and acquired railway concrete track images, randomly selected 2000 images and detected cracks in the image process using proposed Gabor Filter Bank methods. Results: As a result, 94% of detection rate are matched to the actual cracks in same quality and format railway concrete track image. Conclution: The crack detection method using Garbor Filter Bank was confirmed to be effective for crack image including noise in the Korean railway concrete track. This system is expected to become an automated maintenance system in the existing human-centered railway industry.

The Integrity Evaluation of weld zone in railway rails Using Neural Network (신경회로망을 이용한 철도레일 용접부의 건전성평가)

  • 윤인식;임미섭
    • Journal of the Korean Society for Railway
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    • v.6 no.2
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    • pp.81-86
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    • 2003
  • This study proposes the neural network simulator for the integrity evaluation of weld zone in railway rails. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The constructed neural network simulator agrees fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). The Proposed neural network simulator in this study can be used for the integrity evaluation of weld zone in railway rails.

Estimation of Maximum Crack Width Using Histogram Analysis in Concrete Structures (히스토그램 분석을 이용한 콘크리트 구조물의 최대 균열 폭 평가)

  • Lee, Seok-Min;Jung, Beom-Seok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.23 no.7
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    • pp.9-15
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    • 2019
  • The purpose of present study is to assess the maximum width of the surface cracks using the histogram analysis of image processing techniques in concrete structures. For this purpose, the concrete crack image is acquired by the camera. The image is Grayscale coded and Binary coded. After Binary coded image is Dilate and Erode coded, the image is then recognized as separated objects by applying Labeling techniques. Over time, dust and stains may occur naturally on the surface of concrete. The crack image of concrete may include shadows and reflections by lighting depending on a surrounding conditions. In general, concrete cracks occur in a continuous pattern and noise of image appears in the form of shot noises. Bilateral Blurring and Adaptive Threshold apply to the Grayscale image to eliminate these effects. The remaining noises are removed by the object area ratio to the Labeled area. The maximum numbers of pixels and its positions in the crack objects without noises are calculated in x-direction and y-direction by Histogram analysis. The widths of the crack are estimated by trigonometric ratio at the positions of the pixels maximum numbers for the Labeled objects. Finally, the maximum crack width estimated by the proposed method is compared to the crack width measured with the crack gauge. The proposed method by the present study may increase the reliability for the estimation of maximum crack width using image processing techniques in concrete surface images.

Static Tests on Transverse Joints of Precast Prestressed Concrete Bridge Deck (프리스트레스를 도입한 프리캐스트 콘크리트 교량바닥판 연결부에 관한 정적 실험)

  • 정철헌;김영진;김성운;박칠림
    • Magazine of the Korea Concrete Institute
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    • v.10 no.2
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    • pp.109-117
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    • 1998
  • 중트럭통행으로 인한 철근콘크리트 교량바닥판의 열화는 교량구조물을 유지보수하는데 있어서 심각한 문제중 하나이며, 프리캐스트 바닥판을 이용한 교량바닥판의 시공 및 교체 방법이 실용적이며, 효과적인 방법으로 인식되고 있다. 본 연구에서는 프리캐스트 바닥판 사이 연결부에 대한 정적실험을 수행하여 실험부재의 탄성영역 및 극한 상태하에서 프리캐스트 바닥판 사이 교축직각 방향 연결부의 강성 및 강도를 평가하였다. 정적실험결과, 무수측 모르나트를 채움재로 사용한 프리캐스트 바닥판 사이 교축방향 연결부는 교축방향으로 적정량의 프리스트레스를 도입함으로서 일반 현장타설 철근콘크리트 바닥판에 비해서 균열에 대한 사용성이 향상되는 것으로 나타났다.

A Study about the efficient Control against the sexual violence in medical area (의사의 성범죄에 대한 최근 의료법 개정법률안 검토)

  • Jeong, Baekeun
    • The Korean Society of Law and Medicine
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    • v.20 no.2
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    • pp.207-229
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    • 2019
  • It is a general recognition that more serious criminal acts in a certain area of society should be given more serious condemation than the same general crimnal act. In particular, considering the purpose of the medical treatment and the trust relationship between the doctor and the patient, the sexual violence by doctor in medical field can not be placed on the same line as that of the general public. But the special legislation to solve this through criminal legal sanctions is not desirable. The basic principle of criminal law ist ultima ratio, so the principle of supplementality. It means to try to solve by all possible means and finally to enter with punishment. A flat and hasty Reaction without the considering of the speciality of medical treatment will cause serious cracking in that area. In addition, it will not be able to expect desirable results in legal practice by breaking down the legal system. Rather, administrative regulation is more efficient than punishment sanctions. But the best way is autonomous control by members of the medical area. Penalties in criminal law must make an enterance at the last, and administrative regulation should be timely intervene in specific situations through diversification. In conclusion, state interventions should be farthest in order to proceed to autonomous control of medical area.

The Initiation of Slip on Frictional Fractures (마찰 전단면의 전단거동과 에너지방출률)

  • Park, Chi-Hyun
    • Tunnel and Underground Space
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    • v.20 no.5
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    • pp.344-351
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    • 2010
  • Slip along a frictional fracture can be approached as initiation and propagation of a mode II crack along its own plane. Fracture mechanics theories predict that under pure mode II loading initiation will occur when the energy release rate of the fracture attains a critical value ($G_{IIC}$), which is generally taken as a material property. For the past few years the rock mechanics group at Purdue University has investigated experimentally the dependence of $G_{IIC}$ on normal stress and on the frictional characteristics of a fracture. A number of experiments has been conducted first on acrylic, a material that, using photoelastic methods, allows visualization of the stress field ahead of the fracture tip; and later on gypsum, a rock model material with relatively low unconfined compression strength. The experimental investigation has been expanded to include other frictional materials with higher unconfined compression strength. Direct shear tests have been conducted on specimens made with cement paste. New observations together with previous experiments indicate that $G_{IIC}$ can only be considered a material property when the peak friction angle of the discontinuity is similar to the residual friction angle; otherwise the critical energy release rate increases with normal stress.