• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.63-72
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• 2007

The traffic sign on the road should be easy to distinguishable even from far, and should be recognized in a short time. As traffic sign is a very important object which provides important information for the drivers to enhance safety, it has to attract human's attention among any other objects on the road. This paper proposes a new method of detecting the area of traffic sign, which uses attention module on the assumption that we attention our gaze on the traffic sign at first among other objects when we drive a car. In this paper, we analyze the previous studies of psycophysical and physiological results to get what kind of features are used in the process of human's object recognition, especially color processing, and with these results we detected the area of traffic sign. Various kinds of traffic sign images were tested, and the results showed good quality(average 97.8% success).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.645-648
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• 2003

This paper presents an active vision system for on-line traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto lends, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color, intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a large size in the image. The recognition algorithm is designed by intensively using built in functions of an off-the-shelf mage processing board to realize both easy implementation and fast recognition. The results of on-road experiments show the feasibility of the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.471-476
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• 2004

This paper presents an active vision system for on-line traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto lends, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color, intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a large size in the image. The recognition algorithm is designed by intensively using built in functions of an off-the-shelf image processing board to realize both easy implementation and fast recognition. The results of on-road experiments show the feasibility of the system.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.91-98
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• 2011

Road signs are part of the traffic facilities intended to guide drivers to their destinations in a safe and comfortable manner. Due to the creation of new routes, changes to the old routes, and the deterioration of road signs, road signs do require efforts to do ongoing field investigations and put the results in a database. The purpose of this study was to propose methodologies to do field investigations and build a database for road signs efficiently. For that purpose, a mobile mapping system was designed for field investigations. The designed mobile mapping system was comprised of three cameras to produce image information about road signs, GPS/IMU/DMI to obtain information about the position and attitude of a vehicle, and a laser scanner to generate information about the locations of road signs and routes. Also proposed in the study was a procedure to automatically detect the areas of road signs in the road signs images and recognize their characters.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.70-79
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• 2017

This study proposes a method to quickly and accurately acquire distance information on direction signs. The proposed method is composed of the recognition of the sign, pre-processing to facilitate the acquisition of the road sign distance, and the acquisition of the distance data. The road sign recognition uses color detection including gamma correction in order to mitigate various noise issues. In order to facilitate the acquisition of distance data, this study applied tilt correction using linear factors, and resolution correction using Fourier transform. To acquire the distance data, morphological operation was used to highlight the area, along with labeling and template matching. By acquiring the distance information on the direction sign through such a processes, the proposed system can be output the distance remaining to the next junction. As a result, when the proposed method is applied to system it can process the data in real-time using the fast calculation speed, average speed was shown to be 0.46 second per frame, with accuracy of 0.65 in similarity value.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.699-708
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• 2021

In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.21-32
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• 2006

The purpose of this study is to determine the economical standard for road signs by verifying the difference in driver's legibility time with respect to the spacing of letters on the toad signs. Laboratory simulations were conducted to confirm the difference in legibility time for six target signs of different spacing. Also. a binary logit model was used to find the main factors, which could lower the rate if misreading. This model involves not only a simple enlargement of signs but also a suitable match of letters and signs along with the optimal spacing of the text letters on the road signs to increase the legibility of the sign. The result of this study verified the importance of spacing in road signs and Proved itself to be an effective method to determine the future standard for the road signs.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.312-322
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• 2012

The paper presents an approach for recognizing the broken area of the traffic signs. The method is based on the Recognition System for Traffic Signs (RSTS). This paper describes an approach to using the location histogram matching for the broken traffic signs recognition, after the general process of the image detection and image categorization. The recognition proceeds by using the SIFT matching to adjust the acquired image to a standard position, then the histogram bin will be compared preprocessed image with reference image, and finally output the location and percents value of the broken area. And between the processing, some preprocessing like the blurring is added in the paper to improve the performance. And after the reorganization, the program can operate with the GPS for traffic signs maintenance. Experimental results verified that our scheme have a relatively high recognition rate and a good performance in general situation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.117-132
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• 2021

Due to the terrain in Korea, there are many road sections passing through mountainous areas. During the winter, there is a higher risk of traffic accidents, due to black ice caused by the lack of sunlight. Despite domestic road freezing safety measures, accidents caused by road freezing results in severe traffic accidents. Under these considerations, this study analyzed whether traffic safety signs that change in response to the external temperature help drivers recognize frozen road segments. The study was conducted through analysis of the effect of the signs on a driver's perspective. For the signs under development, out of the signs designed by experts, the sign design which received the highest visibility and effectiveness evaluation ratings from the general public was selected. The sign was implemented through Virtual Reality (VR) and installed on the right side of the road to analyze the effect on gazing and driving behavior. As a result of analyzing the driver's driving behavior, a speed reduction of about 7km/h or more was found in the sign section. Therefore, It was found that the existence of the sign had a strong relationship with the rate of the drivers' speed reduction.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.430-443
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• 2013

The recognition of current position and road surrounding of car is very important to driver for safe driving. This paper presents the recognition technique of the road traveling environment using position information hiding and viewpoint transform that monitors the information of road furniture and signature and notifies them to driver. The proposed scheme generates the road images into which the position information are hided, from car camera and GPS module and provides the road information to driver through the viewpoint transformation and the road signature detection. The driving tests with camera and GPS module verified that the position information hiding takes about 66.5ms per frame, the detection rate of road signature is about 95.83%, and the road signature detection takes about 227.45ms per frame. Therefore, we know that the proposed scheme can recognize the road traveling environment on the road video with 15 frame rate.