• Title/Summary/Keyword: Hough transform filter

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Optical hough transform by use of rotationally multiplexed holograms (회전다중 홀로그램을 이용한 광학적 Hough 변환)

  • 신동학;장주석
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.34D no.11
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    • pp.64-69
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    • 1997
  • We have shown that the Hough transform filter can be easily obtained by repeatedly recording one line segment pattern holographically by use of rotational multiplexing. With this filter, one can get resutls of the hough transform in the time of light propagation. To demonstrate our method experimentally, the hough transform filter for 18 different rottion angles was recorded, and experimental transform results were compared with simulated ones for a few input patterns. By introducing a compensation process for the non-uniformity of both the input plane wav eand the diffraction efficiency of each hologram. It is possible to get more precise transform results.

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Optical implementation of the Hough transform for both line and circle parameterization by use of rotationally multiplexed holograms (회전다중 홀로그램을 이용한 선 및 원 파라미터화를 위한 Hough 변환의 광학적 구현)

  • 신동학;장주석
    • Korean Journal of Optics and Photonics
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    • v.9 no.5
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    • pp.321-325
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    • 1998
  • We explain that a holographic filter of the generalized Hough transform can be easily obtained by use of rotational multiplexing in hologram recording. To show the feasibility of our approach experimentally, we recorded the Hough transform filter of both line and circle parameterization by combined use of rotational and angle multiplexing. Experimental results on the Hough transform for a few input patterns are presented.

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Hough Transform Clutter Reduction Algorithm for Piecewise Linear Path Active Sonar Target Detection and Tracking Improvement (구간선형기동 능동소나표적 탐지 추적 성능향상을 위한 허프변환 클러터제거 알고리즘)

  • Kim, Seong-Weon
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.4
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    • pp.354-360
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    • 2013
  • In this paper, it is discussed that the detection and tracking performance of the piecewise linear path underwater target is improved using clutter reduction algorithm in heavy clutter density environment. Through clutter reduction algorithm using Hough Transform, measurements which represent clutter features are removed and the performance of target tracking on the remaining measurements is demonstrated applying CMKF-L(Converted Measurement Kalman Filter with Linearization) as tracking filter. Algorithm performance test is conducted using simulation data and real sea-trial data and by applying the proposed algorithm in heavy clutter density environment, it is confirmed that the target is tracked consistently and stably with clutter rejected measurements.

Optical feature extraction by use of an array of the Hough transform filters (Hough 변환 필터 배열을 이용한 광학적 특징 추출)

  • 장주석;신동학;강영수
    • Korean Journal of Optics and Photonics
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    • v.12 no.1
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    • pp.55-60
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    • 2001
  • We propose a method to extract features optically from the input pattern by use of an array of Hough transfOllli filters. Here the subparts of the input pattern are Hough-transformed by. their cOlTesponding elements of the filter array independently and simultaneously. Compared with the conventional method, in which the whole input pattern is Hough-transformed by a single optical filter, the proposed method not only provides the improved optical transform results when the input pattern becomes complex but also extracts the approximate position information of the line segment features. To show the feasibility of this approach, we fabricated a $5\times5$ filter array and performed preliminary experiments.iments.

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Finding the true length of a line and an ellipse from optical Hough transform results (광학적 Hough변환 결과로부터 직선과 타원의 실제 길이 추출)

  • Park, Sang-Guk;Kim, Seong-Yong;Kim, Su-Jung
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.37 no.3
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    • pp.39-47
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    • 2000
  • In this paper, we propose a new method of finding the true length of the line and long axis of the ellipse at the $\theta$=$\theta$o+ 90$^{\circ}$ and short axis of the ellipse at the $\theta$ = $\theta$o from the Hough transform (HT) results. Through the simulations, we showed that the true length of the line and ellipse could be obtained with 98 % accuracy by using the distance from the maximum envelope to the minimum envelope. To compare the simulation results with the experimental results, we performed optical experiments by using a HT CGH filter. Through the experiments, we showed that our results were very similar to those of the simulation.

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Extracting the Position and the True Length of the Input-Line from Hough Transform data (Hough Transform 정보로부터 입력 직선의 위치와 실제 길이 정보 추출)

  • 김기정;박상국;김종윤;박세준;배장근;김수중
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.301-304
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    • 1999
  • In this paper, we proposed the new method of extracting the position and the length of the input-line by using only two parameters ($\theta$, $\rho$) from the HT(Hough Transform) data. The computer simulations and the optical experiments by using the HT CGH(Computer Generated Hologram) filter is perfermed. The results are very similar to those of the computer simulation results.

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Adult Image Detection Using an Intensity Filter and an Improved Hough Transform (명암 필터와 개선된 허프 변환을 이용한 성인영상 검출)

  • Jang, Seok-Woo;Kim, Sang-Hee;Kim, Gye-Young
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.5
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    • pp.45-54
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    • 2009
  • In this paper, we propose an adult images detection algorithm using a mean intensity filter and an improved 2D Hough Transform. This paper is composed of three major steps including a training step, a recognition step, and a verification step. The training step generates a mean nipple variance filter that will be used for detecting nipple candidate regions in the recognition step. To make the mean variance filter, we converts an input color image into a gray scale image and normalize it, and make an average intensity filter for nipple areas. The recognition step first extracts edge images and finds connected components, and decides nipple candidate regions by considering the ratio of width and height of a connected component. It then decides final nipple candidates by calculating the similarity between the learned nipple average intensity filter and the nipple candidate areas. Also, it detects breast lines of an input image through the improved 2D Hough transform. The verification step detects breast areas and identifies adult images by considering the relations between nipple candidate regions and locations of breast lines.

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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Pupil Detection using PCA and Hough Transform

  • Jang, Kyung-Shik
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.2
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    • pp.21-27
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    • 2017
  • In this paper, we propose a pupil detection method using PCA(principal component analysis) and Hough transform. To reduce error to detect eyebrows as pupil, eyebrows are detected using projection function in eye region and eye region is set to not include the eyebrows. In the eye region, pupil candidates are detected using rank order filter. False candidates are removed by using symmetry. The pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using PCA and hough transform, we select a pair with the smallest similarity measure as final two pupils. The experiments have been performed for 1000 images of the BioID face database. The results show that it achieves the higher detection rate than existing method.

A Study on the Image Processing of Visual Sensor for Weld Seam Tracking in GMA Welding

  • Kim, J.-W.;Chung, K.-C.
    • International Journal of Korean Welding Society
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    • v.1 no.2
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    • pp.23-29
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    • 2001
  • In this study, a preview-sensing visual sensor system is constructed far weld seam tracking in GMA welding. The visual sensor system consists of a CCD camera, a diode laser system with a cylindrical lens, and a band-pass-filter to overcome the degrading of image due to spatters and/or arc light. Among the image processing methods, Hough transform method is compared with the central difference method from a viewpoint of the capability for extracting the accurate feature position. As a result, it was revealed that Hough transform method can more accurately extract the feature positions and it can be applied to real time weld seam tracking. Image processing which includes Hough transform method is carried out to extract straight lines that express laser stripe. After extracting the lines, weld joint position and edge points are determined by intersecting the lines. Even though the image includes a spatter trace on it, it is possible to recognize the position of weld joint. Weld seam tracking was precisely implemented with adopting Hough transform method, and it is possible to track the weld seam in the case of offset angle is in the region of $\pm$ $15^{\circ}$.

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