• Journal of the Korea Computer Industry Society
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• v.8 no.3
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• pp.155-166
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• 2007

In this paper, captured face-image was pre-processing, segmentation, and extracting features from thinning by differential operator and minute-delineation. A straight line in slope-intercept form was transformed at the $r-\theta$ domain using Hough Transform, instead of Housdorff distance are extract feature as length, rotation, displacement of lines from thinning line components by differentiation. This research proposed a new approach compare with Hough Transformation and Housdorff Distance for face recognition so that Hough transform is simple and fast processing of face recognition than processing by Housdorff Distance. Rcognition accuracy rate is that Housdorff method is higher than Hough transformation's method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.11-20
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• 2007

This paper proposes a new efficient method to detect ellipses using a segment merging based Randomized Hough Transform. The key idea of the proposed method is to separate single line segments from an edge image, to estimate ellipses from any pair of the single line segments using Randomized Hough Transform (RHT), and to merge the ellipses. This algorithm is able to accuracy estimate the number of ellipses and largely improves the computational time by reducing iterations.

• Proceedings of the IEEK Conference
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• 2003.07e
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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.

• Plant Journal
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• v.16 no.4
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• pp.33-39
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• 2020

For several decades, productivity in construction industry has been regressed and it is inevitable to improve productivity for major EPC players. One of challenges to achieve this goal is automatically extracting information from imaged drawings. Although computer vision technique has been advanced rapidly, it is still a problem to detect pipe lines in a drawing. Earlier works for line detection have problems that detected line elements be broken into small pieces and accuracy of detection is not enough for engineers. Thus, we adopted Contour and Hough Transform algorithm and reinforced these to improve detection results. First, Contour algorithm is used with Ramer Douglas Peucker algorithm(RDP). Weakness of contour algorithm is that some blank spaces are occasionally found in the middle of lines and RDP covers them around 17%. Second, HEC Hough Transform algorithm, we propose on this paper, is improved version of Hough Transform. It adopted iteration of Hough Transform and merged detected lines by conventional Hough Transform based on Euclidean Distance. As a result, performance of Our proposed method improved by 30% than previous.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1747-1758
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• 2016

In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

• Journal of IKEEE
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• v.20 no.1
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• pp.82-88
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• 2016

The detection rate of Progressive Probability Hough Transform(PPHT) is decreased when a lot of noise components exist due to an unclear or complex original image although it is quite a good algorithm that detects line segments accurately. In order to solve the problem, we propose an improved line detecting algorithm which is robust to noise components and recovers slightly damaged edges. The proposed algorithm is based on PPHT and traces a line segments by pixel and checks of it is straight. It increases the detection rate by reducing the effect of noise components and by recovering edge patterns within a limited pixel size. The proposed algorithm is applied to a lane detection method and the false positive detection rate is decreased by 30% and the line detection rate is increased by 15%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.674-677
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• 2017

The Hough transform is the most representative algorithm for a straight line detection based on edge pixels. It shows excellent performance in a simple linear image but requires a considerable amount of computation in a noisy or complex image and has a problem of detecting a pseudo straight line easily. In this paper, we propose a straight line detection algorithm to solve the problem of the conventional Hough transform. The proposed algorithm detects the straight line information of edge pixels by using principal component analysis (PCA) before performing Hough transform and performs the Hough transform of the limited slope area in the valid edge pixels based on the detected straight line information of edge pixels. Simulation results show that the proposed algorithm reduces the amount of computation as well as eliminates pseudo straight lines.

• 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.

• Proceedings of the Optical Society of Korea Conference
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• 1990.02a
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• pp.121-125
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• 1990

Optical Hough transform technique is introduced to obtain the straight line features in parallel from the input scene images. Experimental results are also provided to demonstrate the advantage of such optical parallel processor over the digital one. Peaks in optical Hough space are free from quantization noise and thus easy to detect.

• Proceedings of the IEEK Conference
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• summer
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• pp.274-275
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• 2004

The Hough transform has been used as a tool for line detection. The main idea of the Hough transform is to transform each pixel in the image individually into the parameter domain. In this way, the Hough transform converts a difficult global detection problem in the image domain into a more easily solved local peak detection problem in the parameter domain. In this paper, we show that the discrete Hough transform is identical to the discrete Radon transform. Thus, we can use the generalized Radon transform to handle more general parameterized curve types.