• International Journal of Internet, Broadcasting and Communication
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• 제15권1호
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.449-452
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• 1998

In this study, the basic image-board and algorithm has been developed to extract a road lane by modeling the driving process. The high speed processing enables an image capture, processing and prompt decision making. In order to high speed processing ASIC like FPGA was designed and integrated in one board system. The algorithm enabling road driving must recognize a straight and bend edge separately. The high speed image processing board using FPGA can be used in real-time decision makeing system for road driving and in the machine vision under bad working environments like a coal mine. And it also can be used in the safety control system in subway and in image input system of CCTV and CATV by designing the board to meet various user's needs.

• 한국정밀공학회지
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• 제16권10호
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• pp.25-34
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• 1999

In this paper, an algorithm is presented to recognize lane and obstacles based on highway road image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, edge detection, and identification of lanes. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction and the presence of absence of an obstacle. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing lane and obstacles. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning of assistance system

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.773-778
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• 1991

In this paper we describe a road following method for an autonomous vehicle. From a road image in gray level, a road boundary is detected using a gradient operator, and then the road boundary is converted to orthogonal view of the road showing the vehicle position and heading direction. In this research an efficient road boundary search technique is developed to support real time vehicle control. Also, an obstacle detection method, using images taken from two different positions, has been developed.

• KIEAE Journal
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• 제3권2호
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• pp.33-36
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• 2003

The influence of the visual information on the sound perception would be considerable. Furthermore, if the sound perception ranges in noisiness or annoyance beyond the loudness, it will depend much more on the shape of the visual information. This paper aims to estimate the influence of the several kinds of visual information on the perception of road traffic noise by means of the psycho-acoustic test method. The findings of present study on the influence of visual information on subjective noise perception are summarized as follows: Presenting visual images of mild and comfortable scenery reduced the noise perception reaction at the less noisy environments not exceeding 65 dB(A). At highly noisy environments exceeding 65 dB(A), however, the noise perception can be reduced by strong image of waterfall. Even eliminating the road traffic image may be helpful. Visual image of waterfall reduced the noise perception at all levels. It is inferred that the road traffic noise perception can be effectively ameliorated by presenting strong and real landscape images at any noisy environment.

• 한국자동차공학회논문집
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• 제10권5호
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• pp.147-159
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• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• Journal of information and communication convergence engineering
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• 제10권4호
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• pp.378-383
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• 2012

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

• 한국정밀공학회지
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• 제18권3호
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• pp.68-74
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• 2001

A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.

• 한국조경학회지
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• 제13권2호
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• pp.37-70
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• 1985

The purpose of this study is to present objective basic data for environmental design by the quantitative analysis of visual quality emboded in physical environment. For this, as for the front garden of high schools, the spatial image was measured by the S.D. Scale Method, Factor Analysis was proceeded by the principal component analysis and the visual preference was investigated by the Paired Comparision Method. The scale values of plain and unpleasant road surface and external appearance of buildings, which are related to emotions of simpleness fell from straightness and stability, were found to be high. But, except for the road surface of Kyunggi High School, scale values of variables explaining the variation of the quality of materials, level of floor and rythm were generally low. For all green spaces, scale values of variables explaining the degree of pleasantness was found to be generally high. And, those explaining tidiness and characteristics of green spaces were not in the same tendency. But, the green spaces of Youngdong High school can be considered to the space with plenty of visual absorption uniqueness were high. As for the correlation between variables, variables for green spaces(12 and 26) and those for overall view of front garden( 1 and 4) revealed high positive correlation. Also, "order - disorder" and "convenient- incovenient" included in road surface variable can be regarded to have the same meaning since the correlation coefficient between them is very high, 0.7045. Image variables including road surface, external appearance of buildings, green spaces and overall view of front garden showed 91.21~61.08% of total variance. Thus, the remains can be considered to be the error valiance or specific variance. In Fctor I, II and III, main components explaining the road surface image of front gardens are order, hardness, texture, color, gradient and rythm. As for the external appearance of b wilding, variables of color, hardness, stability, peculiality and shape revealed high values of factor load. For all variables, communality was drastically high and ellen values and common variance were found to be very high in Factor I. As for the front gardens, variables explaining volume and peculiarity were found to be the main components of Factor I. In Factor II and III, variables of factor load were tidiness, pleasantness.

• 인터넷정보학회논문지
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• 제16권2호
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• pp.49-55
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• 2015

최근 5년간의 주 야간별 교통사고 통계에 따르면 대부분의 자동차 교통사고는 주간보다 야간에 더 많이 발생했다. 교통사고는 다양한 원인으로 발생하게 되는데 그 중 중요한 요소는 조명 미설치 또는 조명 위치의 부적합으로 운전자의 시야 혼란을 야기하여 교통사고를 유발하게 된다. 본 논문은 부적절한 도로 조명 시설 위치와 미설치 구역을 파악하고 관련 정보들을 데이터베이스화 하였다. 이를 위해 운전자의 위치 정보, 주행 정보, 도로 밝기 정보를 스마트폰을 이용하여 실시간으로 데이터베이스 서버에 저장하는 도로 밝기 측정 어플리케이션을 설계 및 구현하였다. 본 어플리케이션은 안드로이드 NDK을 이용하여 Native C/C++ 환경에서 구현되었으며, 이에 따라 자바나 다른 언어로 작성된 어플리케이션 보다 연산속도를 향상시켰다. 도로 밝기를 측정하기 위하여 카메라 영상인 RGB 색 공간의 영상을 YCbCr 색 공간의 영상으로 변환하여 휘도를 측정한다. 이를 위해 먼저 차선을 검출하고 도로 밝기 검출 영역의 휘도 값을 계산하여 데이터베이스에 저장한다. 또한 스마트폰의 카메라를 이용하여 실시간으로 도로의 영상을 입력 받고 도로의 차선부분에 대한 관심영역을 지정하여 연산 속도를 향상시켰다. 관심영역의 영상은 Grayscale 영상으로 변환하고 Canny 에지 검출기를 사용하여 외곽선을 추출하고 Hough line transform을 적용하여 차선의 후보군을 선별한다. 선별된 후보 차선의 기울기를 계산하여 양쪽의 차선을 선정한다. 양쪽 차선이 검출되면 차선의 교차점으로부터 아래로 20픽셀의 높이를 가진 삼각형을 도로 밝기 측정범위로 설정한다. 삼각형 부분의 모든 픽셀에 대한 R, G, B값을 추출하여 Y값을 계산하고 픽셀 밝기 값의 평균을 0부터 100사이의 값으로 계산하여 검은색부터 초록색으로 도로의 밝기를 표현하였다. 계산된 60m 전방의 도로 밝기 값은 스마트폰의 GPS 센서를 통해 측정된 운전자의 주행 정보와 위치 정보를 획득하여 10분 간격으로 무선통신을 통해 데이터베이스 서버에 저장하였다. 향후 수집된 도로 밝기 정보들은 스마트폰 어플리케이션이나 차량 내비게이션을 통해 운전자들에게 조심 운전을 경고하거나 효율적인 도로 조명 관리를 위한 개보수 계획에 반영될 수 있을 것으로 기대된다.