• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2291-2297
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• 2015

This paper presents a vehicle detection system using the video as a input image what has moving of vehicles.. Input image has constraints. it has to get fixed view and downward view obliquely from top of the road. Road detection is required to use only the road area in the input image. In introduction, we suggest the experiment result and the critical point of motion history image extraction method, SIFT(Scale_Invariant Feature Transform) algorithm and histogram analysis to detect vehicles. To solve these problem, we propose using applied Gaussian Mixture Model(GMM) that is the Vehicle Detection GMM(VDGMM). In addition, we optimize VDGMM to detect vehicles more and named VDGMM 2.0. In result of experiment, each precision, recall and F1 rate is 9%, 53%, 15% for GMM without road detection and 85%, 77%, 80% for VDGMM2.0 with road detection.

• Journal of the Korean Institute of Rural Architecture
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• v.13 no.1
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• pp.29-36
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• 2011

This paper aims to clarify the residential quarter organization and housing spatial form of fishing village in Eocheong-do Island. The results are as follows. First, island residential quarter is formed along the coastline, the detached house and the shop house are mainly located in the front of the coastline. Second, the inclination road which connects the northernmost end part and the seashore road is maintained as a road system of a residential quarter from the Japanese colony term until now. Third, It is the feature that Eocheong-do island has the wide width of the front of a site compared with other island residential quarters. Therefore, the frontage wide of a building is also large. Fourth, the entrance of the building where the frontage is mainly located right in the middle, and each rooms are located in the surroundings of it. Finally, the typical community space of Eocheong-do island is Pyeongsang(平床). Pyeongsang is space which receives various functions in inhabitants' life cycle.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.249-257
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• 2017

This paper proposes a method to segment urban scenes semantically based on location prior information. Since major scene elements in urban environments such as roads, buildings, and vehicles are often located at specific locations, using the location prior information of these elements can improve the segmentation performance. The location priors are defined in special 2D coordinates, referred to as road-normal coordinates, which are perpendicular to the orientation of the road. With the help of depth information to each element, all the possible pixels in the image are projected into these coordinates and the learned prior information is applied to those pixels. The proposed location prior can be modeled by defining a unary potential of a conditional random field (CRF) as a sum of two sub-potentials: an appearance feature-based potential and a location potential. The proposed method was validated using publicly available KITTI dataset, which has urban images and corresponding 3D depth measurements.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1411-1412
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• 2015

Detection of road lanes is an important technology, which is being used in autonomous vehicles from last few years. This method is very helpful and supportive for the drivers to provide them safety and to avoid road accidents. Alot of methods are being used to detect road lane markings. We can categorize them into three major categories: sensor-based, feature-based, and model-based methods. And in this study we give the comprehensive survey on lane marking techniques.

• Journal of the Society of Disaster Information
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• v.10 no.2
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• pp.320-334
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• 2014

The government policy had placed new construction as the kernel of the investment in the road department. This had been shifted, however, since the government's budget of the road department reached its peak in 2000, new construction had came to a downsizing phase while the maintenance increased gradually. Considering this recent trend, the necessity of a new paradigm in the road policy had came to a fore, in order to prove the justification of increase in the maintenance budget as well as successfully fulfill the user's needs in the service quality. The developed countries that had intensively constructed social infrastructure in 1950-60s are enjoying a great achievement by applying the asset management concept in coping with the deterioration of the public facilities. This research suggests the basic framework in establishing "Korean Road Asset Management System" designed to efficiently manage the national road. The main feature of this system is to absorb economic analysis course into the current pavement management system, in order to form not only long-lasting but also preventive road management policy.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1369-1382
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• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.145-148
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• 1996

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.19-26
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• 1999

The geographic information system is needed in the image recognition field. This study recommends an efficient method to construct the GIS from the feature extraction of roads through scanning of a normal or hand-made maps. Many algorithms have been presented for such image information recognition. However, such algorithm processes have limitations due to their complexity. To efficiently extract road information from scanning map images. a $3{\times}3$ directional form is applied - structuring element, erosion and dilation, and opening and closing. This method allows for efficient evaluation of the featured road extracts from the map image and from the character sets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.483-491
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• 2013

By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.2 s.20
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• pp.77-85
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• 2002

The intention of this study is to extract the spatial and attribute information of road facility for Geospatial Information System(GIS) using graphic solution. Terrestrial photogrammetry has a lot of possibility for the acquisition of road facility information, which has much convenience in locating camera station, selecting the direction, and taking multiple images of the object at the fixed position. This study intended to develop the technique using single frame images only for the raw image data, being able to apply in the case where comparative high accuracy is not required and rigorous photogrammetric method is not available or rapid acquisition of information is need. As the results, we can find the efficiency in plane feature mapping and determining the dimensions of the road facilities.