• 제어로봇시스템학회논문지
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• 제9권10호
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1988-1991
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• 2003

본 논문에서는 도로 주변의 나무와 건물, 그리고 옆 차선의 차량 등에 의한 그림자의 영향을 최소화하며 차선을 검출할 수 있는 방법을 제안하였다 우선 Hough transform을 수행하는 데 있어서 계산 시간을 줄이기 위하여 에지 영상에서 수평 투영을 통하여 vanishing line을 검출하였으며, vanishing line 아래 부분에서만 Hough transform을 수행하였다. 그리고 차선 검출을 위하여 Hough 평면에서 θ을 16등분하여 rough한 차선을 검출하였으며, 도로 형태에 대한 사전 지식을 이용하여 차선 검출을 시도하였다. 도로 주변상황이 다른 두 종류의 연속 영상들에 의한 실험 결과, 도로형태에 대하여 가정한 사전 지식과 유사한 영상들에 대하여 차선을 정확하게 검출하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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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.

• 융합신호처리학회논문지
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• 제14권2호
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• pp.82-89
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• 2013

본 논문에서는 화상에 존재하는 디지털 직선을 고정밀도로 검출하는 방법을 제안한다. 화상의 크기를 $N{\times}N$로 하면, 이 계산량은 $O(N^4)$이지만 실제 사용하기는 곤란하므로, 검출 정밀도의 열화를 억제하면서 계산량을 $O(N^3)$로 하는 알고리즘을 검토하였다. 국소영역에서 Hough 변환하여 추출된 선분을 연신처리(stretching treatment)하고, 화상으로부터 직선을 검출하는 방법은 길거나 짧은 여러 가지의 직선을 고속으로 검출할 수 있는 훌륭한 방법이지만, 기울어진 선분의 검출 정밀도는 약간 떨어진다. 본 논문에서는 사선의 검출 정밀도를 향상시킨 직선 검출방법을 국소영역에 적용함으로써 처리속도가 감소되지 않고, 직선을 고정밀도로 검출하는 방법에 관해서 논술한다. 실험 결과 제안된 방법은 기존의 방법과 같은 정도 이하의 시간에서 정밀도가 높은 직선을 검출할 수 있다는 것을 확인하였다.

• Journal of Welding and Joining
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• 제19권6호
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• pp.600-607
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• 2001

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc light. For this reason. it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. We controled the wire feeding rate using informations of weld line.

• 대한의용생체공학회:의공학회지
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• 제13권2호
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• pp.115-124
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• 1992

An algorithm has been proposed for the automatic detection of optimal epiand endocardial left ventricular borders from 2-D short axis echocardiogram which is degraded by noise and echo drop out. For the implementation of the algorithm, we modified Ballard's Generalized Hough Transform which can be applicable only for deterministic object border, and newly proposed Fuzzy Hough Transform method. The algorithm presented here allows detection of object whose exact shapes are unknown. The algorithm only requires an approximate model of target object based on anatomical data. To detect the approximate epicardial contour of left ventricle, Fuzzy Hough Transform was applied to the echocardiogram. The optimal epicardial contour was founded by using graph searching method which contains cost function analysis process. Using this optimal epicardial contour and average thickness imformation of left ventricular wall, the approximate endocardial line was founded, and graph searching method was also used to detect optimal endocardial contour.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.297-299
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• 2006

Searching the region of interest on the Hough transform domain is done to determine the real road boundary on the high speed way. The mathematical morphology is employed to obtain the gradient image which is utilized in Hough transform. Many possible candidates of lines could appear on the ordinary road environment and simple selection of the strongest line segments likely to be fault boundary lines. To solve such problem, the search area for the candidates of the road boundary which is called the region of interest is limited on the Hough space. The effectiveness of the proposed algorithm has been shown with experimental results.

• 전자공학회논문지SC
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• 제44권6호
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• pp.11-20
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• 2007

기존 Hough transform을 이용한 타원 검출의 수행 속도와 개수의 추정을 개선하기 위해 본 논문에서는 선분 세그먼트 기반 Randomized Hough Transform (RHT)을 제안한다. 제안하는 방법은 에지 영상을 선분 세그먼트 단위로 분할한 후 임의의 선분 세그먼트 쌍을 RHT를 이용해서 타원을 추정하여 병합여부를 판단한다. 이와 같이 선분 세그먼트 단위로 RHT를 적용하면 적은 반복수행으로 타원을 추정할 수 있으며 복잡한 에지 영상에서도 보다 정확한 타원의 개수를 추정할 수 있다. 제안된 방법의 효율성은 계산속도 및 타원검출의 정확도로 평가하였으며 다양한 입력영상에 대한 실험을 통해 입증하였다.