• Journal of Advanced Marine Engineering and Technology
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• v.30 no.8
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• pp.919-926
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• 2006

To move in unknown or uncertain environment, a mobile robot must collect informations from various sensors and use it to construct a representation of the external world. Ultrasonic sensor can provide range data for this purpose in a simple cost-effective way. However conventional ultrasonic sensor system for a mobile robot are not sufficient for environment recognition because of their large beam opening angle, specular reflection. This paper describe on environmental perception algorithm which can solve these problems in case using ultrasonic sensor. The algorithm consist of two parts. One is to solve beam opening angle problem by fusion from multiple ultrasonic sensors. The other is to cope with specular reflection problem in wall line extract, which is based on Hough Transform. Experiments to verify the validity of the proposed algorithm are carried out, and the results are provided at last part in this paper.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.176-182
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• 2003

The researches for autonomous vehicle have been implemented in many studies, but most studies were confined to the lane fol1owing and changing. This paper addresses a problem of autonomous lane following parking a nonholonomic vehicle. The algorithm for image processing by the hough transform and controlling a steering angle and speed to park a nonholonomic vehicle is developed. The developed system which integrated the control algorithm for parking and vision algorithm for line traction tested with RC car and verified by the performance of the detection of parking area and the reactive parking without collisions.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.3
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• pp.48-57
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• 2005

This paper presents a novel algorithm in order to extract lane-related information based on machine vision techniques. The algorithm makes up for the weak points of the former method, the Edge Distribution Function(EDF)-based approach, by introducing a Lane Boundary Pixel Extractor (LBPE) and the well-known Hough Transform(HT). The LBPE that serves as a filter to extract pixels expected to be on lane boundaries enhances the robustness of machine vision, and provides its results to the HT implementation and EDF construction. The HT forms the accumulator arrays and extracts the lane-related parameters composed of orientation and distance. Furthermore, as the histogram of edge magnitude with respect to edge orientation angle, the EDF has peaks at the orientations corresponding to lane slopes on the perspective image domain. Therefore, by fusing the results from the EDF and the HT the proposed algorithm improves the confidence of the extracted lane-related information. The system shows successful results under various degrees of illumination.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.61-69
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• 2005

This paper presents an efficient method of extracting line segments from the occupancy grids in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities using sonar sensors. We evaluate the orientation information of every grid when the occupancy probability of the grid is updated from sonar range data. To find the shape of an object in the map from orientation information, the orientations are clustered into several groups according to their values. The line segments are, then, extracted from the clusters based on Hough transform. Finally, a feature-based map is built with these line segments. The proposed method is illustrated with the results produced by sets of experiments in an indoor environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1496-1499
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• 2004

The paper persents an efficient method of extracting line segment in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the simplified Bayesian updating model. The probabilities and orientations of cells in the grid map are continuously updated while the robot explorers to their values. The line segments are, then, extracted from the clusters using Hough transform methods. The eng points of a line segment are evaluated from the cells in each cluster, which is simple and efficient comparing to existing methods. The proposed methods are illustrated by sets of experiments in an indoor environment.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1132-1135
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• 1996

The objective of this paper is to make a model-based map for the localization of an autonomous mobile robot(AMR) from ultrasonic sensor measurements, that are acquired when the AMR explores unknown indoors. First, the AMR navigates on unknown space by wall-following and gathers range data from the ultrasonic sensor. Then, the range data are converted to a wall-marked gird map, from which lines representing the walls are extracted using the Hough transform. This process is implemented on an AMR having an ultrasonic sensor, and a preliminary experimental result is presented.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.839-844
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• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.95-104
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• 1999

With the increasing of cars, general studies of them for the traffic safety have been raised as important problems. Visual system to radio-controled driving is to sample road traffic information as reconstructing a model from lots of road traffic information which is successively input in order to drive on unknown road. This paper proposes a sampling process of the road traffic information board needed in automatic driving under automatic drive system using Hough Transform and Genetic Alorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.795-801
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• 1998

In this paper, we propose a machine vision algorithm for inspecting inserts which are used for milling and turning operations. Major defects of the inserts are breakage and crack on insert surfaces. Among the defects, breakages on the face of the inserts can be detected through three stages of the algorithm developed in this paper. In the first stage, a multi-layer perceptron is used to recognize the inserts being inspected. Edge detection of the insert image is performed in the second stage. Finally, in the third stage breakages on the insert face are identified using Hough transform. The overall algorithm is tested on real specimens and the results show that the algorithm works fairly well.