• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.369-377
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• 2008

Though the Hough transform(HT) is a well-known method for detecting analytical shape represented by a number of free parameters, the basic property of the HT, the one-to-many mapping from an image spare to a Hough space, causes the innate problem, the sensitivity to noise. This basic problem also deteriorates the quality of detected lines and makes the detected line deviated from the real one or generates some bogus, multiple lines where only one real line exists. The size of Hough space also affects the quality of detected lines. In this paper, we analyzed the line distortions in the traditional Hough transform and showed that the distortions are relieved in the edge strength Hough transform(ESHT), which is a modified HT. However the usage of expanded edge and edge strength in ESHT can cause some new line distortions which do not exist in the HT. These new ones can be solved by a proper setting of decreasing and broadening parameter values and the optimal values can be determined only by some pre-determined values. We also illustrated several examples to show the distortion-decreasing property of ESHT.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.162-170
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• 2002

Detecting straight lines in an image is frequently required for various machine vision applications such as restoring CAD drawings from scanned images and object recognition. The standard Hough transform has been dominantly used to that purpose. However, massive storage requirement and low precision in estimating line parameters due to the quantization of parameter space are the major drawbacks of the Hough transform technique. In this paper, to overcome the drawbacks, an iterative algorithm based on a self-organizing map is presented. The self-organizing map can be adaptively learned such that image points are clustered by prominent lines. Through the procedure of the algorithm, a set of lines are sequentially detected one at a time. The algorithm can produce highly precised estimates of line parameters using very small amount of storage memory. Computational results for synthetically generated images are given. The promise of the algorithm is also demonstrated with its application to two natural images of inserts.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2234-2236
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• 1998

In this paper, we propose a new algorithm based on multi-resolution application of the parameter space to the Hough transform technique. The existing Hough transform technique employs mapping of fixed parameter space in order to extract straight lines from image. One of the difficulties of the existing Hough transform technique lies in the detection of multiple adjacent lines for only one line. Increasing the parameter space from the low level resolution to the high level resolution, our algorithm detects straight line in a stable and efficient fashion. Experimental results are included to verity the performance of proposed algorithm.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.715-717
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• 2008

The connectivity weighted Hough transform is a useful method for detecting well-connected short lines without generating false lines yet requires extensive computation. This letter describes a method that reduces the computation of the connectivity weighted Hough transform by removing unnecessary weight calculations using the gradient angles of feature points. In simulations with synthetic images and experiments with liquid crystal display panel images, the proposed method showed significantly improved speed without compromising detectability.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.3
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• pp.118-123
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• 1999

Hough transform is well employed to retect or recognize the lines in image processing or in computer vision. Curve of the logarithm of ranges against the bearing does not change its shape according to data trints. This fact suggests that calculation cost can be remarkably reduced. An effective line detection algorithm is represented.sented.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.421-424
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• 2022

Hough transform is a representative algorithm for detecting straight lines in an edge image. It corresponds the parameters of straight lines that may occur in the edge pixel into a parameter space, and detects valid parameters satisfying a given condition as straight lines. In general Hough transform, the parameters of the line are calculated with the image origin as the reference point. However, in this paper, the Hough transform based on the image center as a reference point is performed and its performance is compared and analyzed with the conventional Hough transform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.227-232
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• 2018

In a Hough transform that is a representative algorithm for the straight line detection, a great number of edge pixels generated from noisy or complex images cause enormous amount of computation and pseudo straight lines. This paper proposes a two step straight line detection algorithm to improve the conventional Hough transform. In the first step, the proposed algorithm divides an image into non-overlapping blocks and detects the information related to the straight line of the edge pixels in the block using a principal component analysis (PCA). In the second step, it detects the straight lines by performing the Hough transform limited slope area to the pixels associated with the straight line. Simulation results show that the proposed algorithm reduces average of ${\rho}$ computation by 94.6% and prevents the pseudo straight lines although some additional computation is needed.

• 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.