• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.261-274
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• 2004

The feature extraction using remotely sensed imagery has been recognized one of the important tasks in remote sensing applications. As the high-resolution imagery are widely used to the engineering purposes, need of more accurate feature information also is increasing. Especially, in case of the automatic extraction of linear feature such as road using mid or low-resolution imagery, several techniques was developed and applied in the mean time. But quantitatively comparative analysis of techniques and case studies for high-resolution imagery is rare. In this study, we implemented a computer program to perform and compare GDPA (Gradient Direction Profile Analysis) algorithm and Hough transformation. Also the results of applying two techniques to some images were compared with road centerline layers and boundary layers of digital map and presented. For quantitative comparison, the ranking method using commission error and omission error was used. As results, Hough transform had high accuracy over 20% on the average. As for execution speed, GDPA shows main advantage over Hough transform. But the accuracy was not remarkable difference between GDPA and Hough transform, when the noise removal was app]ied to the result of GDPA. In conclusion, it is expected that GDPA have more advantage than Hough transform in the application side.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.724-728
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• 2005

This paper represents a development of a range finder sensor module for indoor 2-D mapping and modified Hough transformation for map building. A range finder sensor module has been developed by using optic PSD (Position Sensitive Detector) sensor array at a low price. While PSD sensor is cost effective and light weighting, it has switching noise and white noise. To remove these noises, we propose a heuristic filter. For line-based map building, also we proposed advanced Hough transformation and navigation algorithm. Some experiments were illustrated for the validity of the developed system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.558-561
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding Process 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 noise such spatter and arc light. The adaptive Hough transformation was used to extract the laser stripe and to obtain specific weld points In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.774-781
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• 2003

The important factors that cause position error in X-Y robot are inertial force, frictions and spring distortion in screw or coupling. We have to estimate these factors precisely to correct position errors, Which is very difficult. In this paper, we makes systems to inspect metal stencil which is used to print solder paste on pads of SMD of PCB with low precision X-Y robot and vision system. To correct position error that is caused by low precision X-Y robot, we defines position error vector that is formed with position of objects that exist in reference and camera image. We apply MHT(Modified Hough Transformation) for the aim of determining the dominant position error vector. We modify reference image using extracted dominant position error vector and obtain reference image that is the same with camera image. Effectiveness and performance of this method are verified by simulation and experiment.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.2
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• pp.309-314
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• 1987

Using computer picture processing, a method of extracting the region of a car number plate is described. A modified Hough transformation, in which parameter plane is restricted, is proposed. The demerits of Hough transformation, i.e., it requires much computation time and storage capacity, are reduced by this method. Further, taking the features of a car number plate into consideration, the region of a car number plate is extracted.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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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.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.77-80
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• 1991

This paper proposes a new feature extraction method which is effectively used in character recognition, and validate the effectiveness through various computational methods for similiarity degree. To get feature vectors used in this method, Hough transform is applied to character image, which is used for edge extraction in image processing. By that transformation technique, strokes could be extracted and feature vectors constructed suitably. The characteristic of this method is solving the difficulties in stroke extraction through transform space analysis, which is induced by noise and blurring, and representing high recognition rate 99.3% within 10 candidates in relative low dimension.

• International Journal of Contents
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• v.7 no.4
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• pp.24-29
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• 2011

In this paper, we propose a method to segment the bottle label in images taken by mobile phones using multi-gradient approaches. In order to segment the label region of interest-object, the saliency map method and Hough Transformation method are first applied to the original images to obtain the candidate region. The saliency map is used to detect the most salient area based on three kinds of features (color, orientation and illumination features). The Hough Transformation is a technique to isolated features of a particular shape within an image. Therefore, we utilize it to find the left and right border of the bottle. Next, we segment the label based on the gradient information obtained from the structure tensor method and edge method. The experimental results have shown that the proposed method is able to accurately segment the labels as the first step of product label recognition system.