• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1479-1484
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• 2005

This paper represents an intelligent sensor controller of mobile robot for object recognition in an indoor hon environment. A range finder sensor module has been developed by using optic PSD (Position Sensitive Detector) sensor way at a low Vice. 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 prorosed advanced Hough transformation and navigation algorithm. Some experiments were illustrated for the validity of the developed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.191-194
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• 2005

This paper represents an intelligent sensor controller of mobile robot for object recognition in an indoor known environment. 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 while noise. To remove these noises, we propose a heuristic filter. For line-based map building, also we proposed advanced Hough transformation and navigation algorism. Some experiments were illustrated for the validity of the developed system.

• International Journal of Contents
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• v.6 no.4
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• pp.1-7
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• 2010

Natural images often contain useful information about the scene such as text or company logos placed on a rectangular shaped plane. The 2D images captured from such objects by a camera are often distorted, because of the effects of the perspective projection camera model. This distortion makes the acquisition of the text information difficult. In this study, we detect the rectangular object on which the text is written, then the image is restored by removing the perspective distortion. The Hough transform is used to detect the boundary lines of the rectangular object and a bilinear transformation is applied to restore the original image.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.807-812
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• 1999

Locating of reinforcing bars, in particular to know their accurate depths, is very important thing in radar inspection of concrete structures. By the way, a depth estimation of reinforcing bars in concrete structures by the radar is not easy because micorwave propagation velocity in test area is generally unknown. This problem can be solved by Generalized Hough transformation technique. Using this technique, the micorwave 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.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.1-99
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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 Laplacian 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 t...

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2213-2216
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• 2003

In this paper, we propose the face identification method which is robust for lighting based on the feature points method. First of all, the proposed method extracts an edge of facial feature. Then, by the hough transform, it determines ellipse parameters of each facial feature from the extracted edge. Finally, proposed method performs the face identification by using parameters. Even if face image is taken under various lighting condition, it is easy to extract the facial feature edge. Moreover, it is possible to extract a subject even if the object has not appeared enough because this method extracts approximately the parameters by the hough transformation. Therefore, proposed method is robust for the lighting condition compared with conventional method. In order to show the effectiveness of the proposed method, computer simulations are done by using the real images.

• International Journal of Contents
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• v.6 no.1
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• pp.6-11
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• 2010

Recently, there has been research to use portable digital camera to recognize objects in natural scene images, including labels or marks on a cylindrical surface. In many cases, text or logo in a label can be distorted by a structural movement of the object on which the label resides. Since the distortion in the label can degrade the performance of object recognition, the label should be rectified or restored from deformations. In this paper, a new method for label detection and restoration in digital images is presented. In the detection phase, the Hough transform is employed to detect two vertical boundaries of the label, and a horizontal edge profile is analyzed to detect upper-side and lower-side boundaries of the label. Then, the biquadratic transformation is used to restore the rectangular shape of the label. The proposed algorithm performs restoration of 3D objects in a 2D space, and it requires neither an auxiliary hardware such as 3D camera to construct 3D models nor a multi-camera to capture objects in different views. Experimental results demonstrate the effectiveness of the proposed method.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.188-199
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• 2013

This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions- horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.1-8
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• 2000

Point pattern matching schemes for finger print recognition do not guarantee robust matching performance for fingerprint Images of poor quality We present a finger print recognition scheme, where transformation parameters of matched ridge pairs are estimated by Hough transform and the matching hypothesis is verified by a new measure of the matching degree using selective directional information Proposed method may exhibit extremely low FAR(False accept rate) while maintaining low reject rate even for the Images of poor quality because of the robustness to the variation of minutia points.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.140-146
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• 2014

This paper introduces a dual-arm robot painter system which is capable of sketching a camera-captured image with short line segments. To express various curved edges in the image by combining line segments, we first apply edge detection algorithm to the entire image, split the edged image into small boxed pieces, and then apply Hough Transformation to each piece so that the edges inside the piece can be approximated with short line segments. To draw the picture within a reasonable time, we designed a simple dual-arm robot system and controlled both arms concurrently according to linear interpolation algorithm. From the experiments, we could verify that simple linear motions can describe various images effectively with a unique brush style.