• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1868-1873
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• 2021

This paper proposes the Hough transform(HT) using an extended lookup table(LUT) to reduce the computational burden of the HT that is a typical straight line detection algorithm, and analyzes its performance. The conventional HT also uses a LUT to the calculation of the parameter 𝜌 of all straight lines passing through an edge pixel of interest(ePel) in order to reduce the computational burden. However, the proposed HT adopts an extended LUT that can be applied to straight lines across the ePel as well as its peripheral edge pixels to induce more computational reduction. This paper proves the validity of the proposed algorithm mathematically and also verifies it through simulation. The simulation results show that the proposed HT reduces the multiplication computation from 49.6% up to 16.1%, depending on the image and the applied extended LUT, compared to the conventional HT.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.153-159
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• 2010

This article presents a method that improve the drive-license test system, especially the course-driving by using the image processing. Decision(pass or not) is recorded and informed to test-driver after the image processing such as image capture, grayscaling, normalization, Hough transform and decision. That result system enables us to manage much more economically and effectively.

• 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.

• 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.

• Journal of the Korea Concrete Institute
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• v.12 no.1
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• pp.23-31
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• 2000

Locating reinforcing bars, in particular to know their accurate depths, is very important in radar inspection of concrete structures. By the way, an accurate depth estimation of reinforcing bars in concrete structures by the radar is not easy because the microwave propagation velocity in test area is generally unknown. This problem can be solved by generalized Hough transformation technique. Using this technique, the microwave propagation velocity in test area can be detected from the radar image, which appear as hyperbolas conveying the velocity information in their shape. A developed speed-up technique for the computation of the Generalized Hough transformation is also investigated in this study. As a result, although it becomes difficult to locate reinforcing bars when multiple parallel bars lying too close together, there is a possibility of detecting accurate depths of reinforcing bars in test area by the proposed method

• 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.

• Journal of Biomedical Engineering Research
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• v.13 no.2
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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.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1171-1180
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• 1995

In this paper, we present a 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In object modeling step, the features for recognition are extracted from the CAD models of objects to be recognized. Since the approach is based on the CAD models, the accuracy and flexibility are greatly improved. In matching stage, the sensed image is compared with the stored model, which is assumed to yield a distortion (location and orientation) in the 3-D Hough transform domain. The high dimensional (6-D) parameter space, which defines the distortion, is decomposed into the low dimensional space for an efficient recognition. At first we decompose the distortion parameter into the rotation parameter and the translation parameter, and the rotation parameter is further decomposed into the viewing direction and the rotational angle. Since we use the 3-D Hough transform domain of the input images directly, the sensitivity to the noise and the high computational complexity could be significantly alleviated. The results show that the proposed 3-D object recognition system provides a satisfactory performance on the real range images.

• 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.