• Title/Summary/Keyword: a hough transform

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Anomaly detection of isolating switch based on single shot multibox detector and improved frame differencing

  • Duan, Yuanfeng;Zhu, Qi;Zhang, Hongmei;Wei, Wei;Yun, Chung Bang
    • Smart Structures and Systems
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    • v.28 no.6
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    • pp.811-825
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    • 2021
  • High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

Iris detection using Hough transform and separable filter (허프 변환과 분리필터를 이용한 홍채 검출)

  • Kim, Tae-Woo;Bae, Cheol-Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.3 no.2
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    • pp.3-11
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    • 2010
  • In this paper we propose a new algorithm to detect the irises of both eyes from a human face. Using the separability filter, the algorithm first extracts blobs(intensity valleys) as the candidates for the irises. Next, for each pair of blobs, the algorithm computes a cost using Hough transform and separability filter to measure the fit of the pair of blobs to the image. And then, the algorithm selects a pair of blobs with the smallest cost as the irises of both eyes. As the result of the experiment using 150 faces images without spectacles, the success rate of the proposed algorithm was 97.3% for the best case and 95.3% for the worst case.

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Iris detection using Hough transform and separable filter (허프 변환과 분리필터를 이용한 홍채 검출)

  • Park, Ho-Sik;Bae, Cheol-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.3
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    • pp.526-534
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    • 2006
  • In this paper we propose a new algorithm to detect the irises of both eyes from a human face. Using the separability filter, the algorithm first extracts blobs(intensity valleys) as the candidates for the irises. Next, for each pair of blobs. the algorithm computes a cost usings Hough transform and separability later to measure the fit of the pair of blobs to the image. And then, the algorithm selects a pair of blobs with the smallest cost as the irises of both eyes. As the result of the experiment using 150 faces images without spectacles, the success rate of the proposed algorithm was 97.3% for the best case and 95.3% for the worst case.

An Improved Hough Transform Using Valid Features (유효 특징점을 이용한 개선된 허프변환)

  • Oh, Jeong-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.9
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    • pp.2203-2208
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    • 2014
  • The Hough transform (HT), that is a typical algorithm for detecting lines in images, needs considerable computational costs and easily detects pseudo-lines on the real world images, because of the large amount of features generated by their complex background or noise. This paper proposes an improved HT that add a preprocessing to estimate the validity of features to the conventional HT. The feature estimation can remove a lot of inessential features for the line detection using a pattern of $3{\times}3$ block features. Experiments using various images show that the proposed algorithm saves computational costs by removing 14%~58% of features depending on images and besides it is superior to the conventional HT in valid line detection.

Application of the Optical Hough Transform for the Detection of a General Ellipse (일반 타원의 검출을 위한 광학적 Hough변환의 적용)

  • Park, Sang-Gug;Kim, Sung-Yong;Kim, Soo-Joong
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.37 no.8
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    • pp.67-75
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    • 2000
  • In this paper, we proposed a new method to find dive parameters of an ellipse from the optical Hough transform (HT) results. The method employs the HT for detection of a straight line and the one-dimensional analysis of the resultant parameter domain. Using this algorithm, we simulated about the ellipses with different positions, and obtained the information of the ellipse with 94% accuracy in the worst case. To compare the simulation results with the experimental ones, we performed optical experiments using a HT Computer Generated Hologram (CGH) filter. Through the experiments, we showed that our results were very similar to the simulation results.

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Performance Evaluation of the Generalized Hough Transform (일반화된 허프변환의 성능평가)

  • Chang, Ji-Young
    • Journal of Convergence for Information Technology
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    • v.7 no.6
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    • pp.143-151
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    • 2017
  • The generalized Hough transform(GHough) can be used effectively for detecting and extracting an arbitrary-shaped 2-D model in an input image. However, the main drawbacks of the GHough are both heavy computation and an excessive storage requirement. Thus, most of the researches so far have focused on reducing both the time and space requirement of the GHough. But it is still not clear how well their improved algorithms will perform under various noise in an input image. Thus, this paper proposes a new framework that can measure the performance of the GHough quantitatively. For this purpose, we view the GHough as a detector in signal detection theory and the ROC curve will be used to specify the performance of the GHough. Finally, we show that we can evaluate the GHough under various noise conditions in an input image.

A Study on Automatic Seam Tracking using Vision Sensor (비전센서를 이용한 용접선 자동추적에 관한 연구)

  • 조택동;양상민;전진환
    • Journal of Welding and Joining
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    • v.16 no.6
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    • pp.68-76
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    • 1998
  • A CCD camera with a laser stripe was applied to realized the automatic weld seam tracking. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path. The adaptive Hough transformation was used to extract laser stripes an to obtain specific weld points. It takes relatively long time to process image on-line control using the basic control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The dead zone, where the sensing of weld line is impossible, was eliminated by rotating the camera with its rotating axis centered at the weld torch. When weld lines were detected, the camera angle was controlled in order to get the minimum image data for sensing of weld lines. Consequently, the image processing time was reduced.

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Recognition of the Center Position of Electric Line Using Modified Hough Transform (수정 하후변환을 이용한 전선의 중심위치의 인식)

  • 안경관
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.1
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    • pp.99-106
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    • 2003
  • Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the there dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The insertion task of an electric line into a sleeve is selected as the typical task of the maintenance of active electric power distribution lines in this paper. A modified hough transform is applied to the recognition of the center of electric line and optimal target position calculation method is newly derived in order to recognize the center 3 dimensional position of the electric line. By the proposed method, it is proved that the center position of the electric line can be recognized without respect to the noise of image and the shape of electric lines and the insertion task of an electric tine is realized.

A Statistical Analysis Method for Image Processing Errors in the Position Alignment of BGA-type Semiconductor Packages (BGA형 반도체 패키지의 위치정렬용 영상처리기법 오차의 통계적 분석 방법)

  • Kim, Hak-Man;Seong, Sang Man;Kang, Kiho
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.984-990
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    • 2013
  • Pick and placement systems need high speeds and reliability for the position alignment process of semiconductor packages in picking up and placing them on placement trays. Image processing is usually adopted for position aligning where finding out the most suitable method is considered most important aspect of the process. This paper proposes a method for judging the performance of different image processing algorithms based on the PCI (Process Capability Index). The PCI is an index which represents the error distribution acquired from many experimental data. The bigger the index, the more reliable the results or the lower the deviation. Two compared and candidate methods are Hough Transform and PCA (Principal Component Analysis), both of which are very suitable for oblong or rectangular type packages such as BGA's. Comparing the two approaches through a CPI with enough experimental results leads to the conclusion that the PCA is much better than the Hough Transform in not only reliability, but also processing speed.

Automated Lineament Extraction and Edge Linking Using Mask Processing and Hough Transform.

  • Choi, Sung-Won;Shin, Jin-Soo;Chi, Kwang-Hoon;So, Chil-Sup
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.411-420
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    • 1999
  • In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

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