• Transportation Technology and Policy
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• v.7 no.3
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• pp.15-18
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• 2010

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.55-65
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• 2006

The ratio of Pedestrians in traffic accident fatality takes up 43% in Korea, which is 2.5 times as much as OECD's average. The traffic accidents features by road type shows that the fatality of the national highway posts the highest due to the accidents of pedestrians. Accordingly, the establishment of safety facilities for pedestrians is expected to increase on the rural roads for the prevention of pedestrian accidents. However, studies on pedestrians have been mainly focused on urban intersections. In Particular, studies on estimating the effectiveness of safety features for pedestrians are very poor. Thus, in this study. the Pedestrian accident probability model on four lane national highway was developed by using logit model. Also, this study analyzed and proposed the effect of facilities as a relative risk by using an odds ratio. As a result of the analysis, the Improvement of sight distance, installing sidewalks and lightings were proven effective alternatives for reducing the pedestrian accidents.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.50-59
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• 2014

This paper proposes a method of localization of vehicle especially the horizontal position for the purpose of recognizing the driving lane. Through tracking road signs, the relative position between the vehicle and the sign is calculated and the absolute position is obtained using the known information from the regulation for installation. The proposed method uses Kalman filter for road sign tracking and analyzes the motion using the pinhole camera model. In order to classify the road sign, ORB(Oriented fast and Rotated BRIEF) features from the input image and DB are matched. From the absolute position of the vehicle, the driving lane is recognized. The Experiments are performed on videos from the highway driving and the results shows that the proposed method is able to compensate the common GPS localization errors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.786-799
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• 2021

Road damage detection is important for road maintenance. With the development of deep learning, more and more road damage detection methods have been proposed, such as Fast R-CNN, Faster R-CNN, Mask R-CNN and RetinaNet. However, because shallow and deep layers cannot be extracted at the same time, the existing methods do not perform well in detecting objects with fewer samples. In addition, these methods cannot obtain a highly accurate detecting bounding box. This paper presents a Multi-level Feature Pyramids method based on M2det. Because the feature layer has multi-scale and multi-level architecture, the feature layer containing more information and obvious features can be extracted. Moreover, an attention mechanism is used to improve the accuracy of local boundary boxes in the dataset. Experimental results show that the proposed method is better than the current state-of-the-art methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.993-1001
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• 2011

Unmanned ground vehicle for facility protection mostly uses model of territory for autonomous navigation. However, modeling of territory using several sensors is highly time consuming and sometimes inefficient for road application. Therefore, an estimation of drivable path based on features of road is required for high speed autonomous navigation on road. In this paper, an estimation method of drivable path using camera and 2D laser rangefinder is proposed. First, a vanishing point is estimated based on image data from CCD camera. Second, a road width is estimated based on range data from 2D laser rangefinder. Finally, the drivable path is estimated by fusing the vanishing point and the road width. The proposed method is tested on both well-structured road and unpaved road like cross-country situation.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Acta Via Serica
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• v.6 no.2
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• pp.61-90
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• 2021

Recent excavations in Qinghai Province, China, have disclosed textiles and artworks from Tuyuhun-Tubo (Tibetan) tombs, dated to the 7^th-9^th centuries, that suggest artistic and cultural exchanges along an external southern branch of the main Silk Road, between Gansu and Sichuan Provinces, across the Qinghai-Tibetan plateau toward the Himalayas. Many similar textiles, possibly from this area, have appeared lately on the art market and ended in private collections. Although these textiles, dated to the early Tibetan period, follow a popular prototype established in Central Asia in the 6^th century, the technical features, colors, and other indigenous elements suggest that they were woven in workshops different from those established between Sogdiana and Gansu. The exhibition "Cultural Exchange Along the Silk Road - Masterpieces of the Tubo Period," organized by the Dunhuang Research Academy and the Pritzker Collaborative Art between July and October 2019 in Dunhuang, Gansu, was a groundbreaking event that gathered scholarly attention on early Tibetan material culture, but a relevant publication is still forthcoming. In my previous work, I briefly discussed a group of silk textiles, possibly from Qinghai or Sichuan, that I analyzed in 2014 in the China National Silk Museum in Hangzhou, Zhejiang. In light of the recent material excavated, published online, or displayed in Dunhuang, in this article, I reevaluate the data previously collected, and discuss in detail the technical and iconographic features of one of the fragments held in Hangzhou. Eventually, the piece was recognized as the ending part of a large panel, which is now in the Abegg Stiftung in Riggisberg, Switzerland.

• Spatial Information Research
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• v.15 no.3
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• pp.335-346
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• 2007

Road sign is one of the road attached facilities to provide conveniences to motor drivers. The setup of location information according to the related regulation and the inclusion of various attributes such as place names, route numbers, symbols, bearings, distances to the place of interest distinguish the road sign from other facilities. These features give advantages to the informationization of road sign. Presently there established about 130,000 road signs on each class of roads, and about 280 road management offices have controlled these road signs independently, but there are plethora of ineffectiveness such as the lack of consistency, recognition, connectivity, and location suitability etc. These are the major factor of confusions rather than providing conveniences, and arisen a lot of public grievances. Accordingly, in this research the road signs throughout the nation were databased and the web-GIS based road sign management system was established to ameliorate the problems reveled. Since the road sign management system we developed reflected the demands of the persons in charge and users, the management effectiveness might be enhanced and the public inconveniences will be reduced.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.121-124
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• 2000

We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing Information from these detectors. The second is hybrid step, we Identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.