• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.1 s.114
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• pp.1-9
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• 2006

The purposes of this study are to develop the concept and the measurement method of IGS(Index of Greenness in Streetscape) and to analyze the present condition of street environments through field surveys of IGS in Seoul. IGS is a new index which directly expresses human's perceptions of plants in a street and defined as the area ratio of which leaves of plants occupy in an eye-level view of a person standing on the center line of a street. In practice, IGS can be calculated from a photograph taken from a center point of a street at about 1.5 meter height from the ground with single lens reflex camera equiped with 50mm standard lens. The photograph must have a special composition in a way that the center point of the photograph is positioning at the visual vanishing point of street center line. Then the IGS can be calculated by computing the percentage of the area covered with the plant leaves in the photograph. Types of streets in Seoul were classified according to road functions into 4 types. We performed field surveys and calculated IGSs from 300 sample sites in Seoul. Followings summarize some of study results. The average IGSs for arterial roads, highways, alleys and back streets are 16.91%, 16.33%, 13.97% and 7.50% respectively. The difference of average IGS values between Ginkgo biloba and Platanus occidentalis was relatively large. From observation IGSs from April 4th, 2003 to October 2nd, 2003, it was evident that the range and timing of each plant species' IGS change is not the same. According to questionnaire to public officials taking charge of street greening, the current evaluated IGS is 24.4%, and it is expected to be 40.7% in the future.

• Korean Institute of Interior Design Journal
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• v.26 no.2
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• pp.3-12
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• 2017

This study has analyzed the features of attention to spacial composition seen in "Seeing ${\leftrightarrow}$ Seen" Correlation of continuous move in the space. The eye-tracking was employed for collecting the data of attention features to the space so that the correlation between visual perception and space could be estimated through the attention features to the difference between spacial composition and display. First, it was confirmed that the attention features varied according to the structure of shops and the exposure degree of selling space, which revealed that, while causing the customers' less attention to both sides of shops, the vanishing-point structure characteristically made their eyes focused on the central part. Second, their initial observation activities were found to be active at the height of their eyes. Third, 10 images were selected as objects for continuous experiment. There was a concern that the central part of each image would be paid intense attention to during the initial observation, but only two of those were found to be so. Fourth, there had been a study result of eye-tracking experiment that the attention had been concentrated on the central part of the image first seen. This study, however, revealed that such phenomenon is limited to the first image. Accordingly, it is necessary to draw up such method for ensuring reliability in order to use the data acquired from any eye-tracking experiment as exclusion of the initial attention time to the first image or of unemployment of the initial image-experiment to analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.797-807
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• 2008

This paper proposes a new algorithm of extracting forward vehicle areas using the acquired lanes and road area information on road images with complex background to improve the efficiency of the vehicle detection. In the first stage, lanes are detected by taking into account the connectivity among the edges which are determined from a method of chain code. Once the lanes proceeding to the same direction with the running vehicle are detected, neighborhood roadways are found from the width and vanishing point of the acquired roadway of the running vehicle. And finally, vehicle areas, where forward vehicles are located on the road area including the center and neighborhood roadways, are extracted. Therefore, the proposed scheme of extracting forward vehicle area improves the rate of vehicle detection on the road images with complex background, and is highly efficient because of detecting vehicles within the confines of the acquired vehicle area. The superiority of the proposed algorithm is verified from experiments of the vehicle detection on road images with complex background.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1247-1255
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• 2016

The safety and autonomous flight function of micro UAV or drones is crucial to its commercial application. The requirement of own building stable drones is still a non-trivial obstacle for researchers that want to focus on the intelligence function, such vision and navigation algorithm. The paper present a GCS using commercial drone and hardware platforms, and open source software. The system follows modular architecture and now composed of the communication, UI, image processing. Especially, lane-keeping algorithm. are designed and verified through testing at a sports stadium. The designed lane-keeping algorithm estimates drone position and heading in the lane using Hough transform for line detection, RANSAC-vanishing point algorithm for selecting the desired lines, and tracking algorithm for stability of lines. The flight of drone is controlled by 'forward', 'stop', 'clock-rotate', and 'counter-clock rotate' commands. The present implemented system can fly straight and mild curve lane at 2-3 m/s.