• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.125-134
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• 2004

This paper proposes a method for recognition of traffic signs using wavelet transform and shape information from the segmented traffic sign regions. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic sign regions based on their symmetries on X- and Y-axes. In the recognition stage, it utilizes shape information including moment edge correlogram and the number of crossings which concentric circular patterns from region center intersects with frequency information extracted by wavelet transform It finally performs recognition by measuring similarity with the templates in the database. The experimental results show the validity of the proposed method from geometric transformations and environmental factors.

• Journal of information and communication convergence engineering
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• v.10 no.4
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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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.41-51
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• 2010

In the research for driver assistance systems, traffic sign information to the driver must be a very important information. Therefore, the detection system of traffic signs located on the road should be able to handel real-time. To detect the traffic signs, color and shape of traffic signs is to use the information after images obtained using the CCD camera. In the road environment, however, using color information to detect traffic sings will cause many problems due to changes of weather and environmental factors. In this paper, to solve it, the candidate traffic sign regions are detected from road images obtained in a variety of the illumination changes using the HSI eign-color model. And then, using the invariant moment-based SVM classifier to detect traffic signs are proposed. Experimental results show that, traffic sign detection rate is 91%, and the processing time per frame is 0.38sec. Proposed method is useful for real-time intelligent traffic guidance systems can be applied.

• Journal of IKEEE
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• v.16 no.4
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• pp.356-363
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and traffic sign recognition is one of them. It can provide important information for safety driving. In this paper, we propose a method for traffic sign detection and identification concentrating on reducing the computation time. First, potential traffic signs are segmented by color threshold, and a polygon approximation algorithm is used to detect appropriate polygons. The potential signs are compared with the template signs in the database using SURF and ORB feature matching method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.437-444
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• 2012

This study intended to improve traffic safety in work zones using fluorescent orange color traffic signs. For this end, the current problems of existing traffic signs and facilities in work zones were analyzed and some good examples of foreign countries were compared. More specifically, in order to identify current problems, the basic shape and color of traffic signs in use were examined through literature review, surveys and field studies. It was found that the fluorescent color worked more effectively than other colors in terms of visibility and conspicuity in work zone sign system. For evaluation, both Conspicuity surveys and in-door simulator experiments were conducted to effectively assess the merits and demerits of different types of traffic signs for work zones. The results of evaluations showed that black lettering on a fluorescent orange background outperformed more than 70% in terms of visibility and ability to call drivers' attention compared with those from black/red lettering on yellow/white backgrounds currently used at work zones on expressways and national highways. In addition, simulated driving experiment disclosed that drivers recognized the fluorescent orange background sign 15m ahead compared with the yellow background sign and 25m ahead compared with the white background sign, respectively. As for the diamond-shaped "Under Construction" sign, drivers recognized fluorescent orange background 11m ahead compared with the yellow background sign and 19m ahead compared with the white background sign, respectively.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.251-256
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• 2015

In this paper, an systematic approach is presented, in which the bridge-type traffic sign structure is body out by CSDDA PrePost Processor. There is dead load and wind load that is working on the structure which will make force and moment. Analyzied the stress distribution of the standard form and by changing the shape, compared the safety in terms of deflection and stress (with the standard form) to know the effect of each component in the bridge-type traffic sign structure. The safety of deflection and stress is evaluated by maximum distance/100) and ASIC code respectively. The standard form of bridge-type traffic sign structure is established by two pairs of pillar and two pairs of floor beam. Replaced the links which is consist of flange and screws as the torsion spring and nm our analysis program. By adjusting variable of rigidity modulus of torsion spring, moment between column and beam is controled depending on value of rigidity modulus.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1268-1279
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• 2005

The current method for pavement sign marking operations is labor-intensive and very dangerous due to the exposure of workers to passing traffic. It also requires blocking traffic for a long period of time resulting serious traffic jam. This paper deals with the development of a robotic system for automating the pavement sign painting operations. The robotic system consists of gantry frame equipped with transverse drive rail and automatic paint spray system. The workspace of the gantry robot is extended to one-lane width with the transverse rail system. This research also includes the development of font data structures that contain the shape information of pavement signs, such as Korean letters, English letters and symbols. The robot path is generated with this font data through the procedures of scaling up/down and partitioning the signs to be painted depending on the workspace size.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1630-1636
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• 2022

The results of current method of traffic sign detection gets hindered by environmental conditions and the traffic sign's condition as well. Therefore, in this paper, we propose a method of improving detection performance of damaged traffic signs by utilizing Hopfield Network and Fuzzy Max-Min Neural Network. In this proposed method, the characteristics of damaged traffic signs are analyzed and those characteristics are configured as the training pattern to be used by Fuzzy Max-Min Neural Network to initially classify the characteristics of the traffic signs. The images with initial characteristics that has been classified are restored by using Hopfield Network. The images restored with Hopfield Network are classified by the Fuzzy Max-Min Neural Network onces again to finally classify and detect the damaged traffic signs. 8 traffic signs with varying degrees of damage are used to evaluate the performance of the proposed method which resulted with an average of 38.76% improvement on classification performance than the Fuzzy Max-Min Neural Network.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.116-117
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• 2004

• Journal of Korean Society of Transportation
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• v.9 no.2
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• pp.101-120
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• 1991

The Subject of this research work is to study the driver's vision and eye-movement ch-aracteristics under the diffrent condiction of road traffic and driving. The analysis of this investigation was conducted spatially or temporaly into three parts'eye-mark distribution, viewing-time percentage and fixation duration. This dissertation focuses on analysis of dr-iver's visual characteristics to improve road circumstamces. In this study driver's ch-aracteristics are measured with eye-mark recorder and analyzed statistically The main features of this study are : 1st Duration distribution of fixation point is significant in 87% at 5% of the significant level in Gamma Distribution. The average of fixation duration by road are 0.33sec on streets 0.45sec on Roads and 0.86sec on highways. The average of fixation duration by visual objects are 0.4sec on road surface 0.26sec on road shoulder 0.49sec on traffic sign 0.37sec on warning sign and 0.67sex on gwide sign. 2st Moving anglrs of a fixation point are fit in the Exponential Distribution. The average moving angle is appeared to be 3.85。 on streets 2.81。 on roads 2.73。 on highway and 5 。 on intersecyion. 3st As a result of examining alignment of guide and warning sign in traffic signs cxisting foundation methods are less affected by lane than by apeed of a vehicle.