• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.125-131
• /
• 2019

A vanishing point is a point on an image to which parallel lines projected from a real space gather. A vanishing point in a road space provides important spatial information. It is possible to improve the position of an extracted lane or generate a depth map image using a vanishing point in the road space. In this paper, we propose a method of detecting vanishing points on images taken from a vehicle's point of view using Deep Neural Network (DNN) and Histogram of Oriented Gradient (HoG). The proposed algorithm is divided into a HoG feature extraction step, in which the edge direction is extracted by dividing an image into blocks, a DNN learning step, and a test step. In the learning stage, learning is performed using 2,300 road images taken from a vehicle's point of views. In the test phase, the efficiency of the proposed algorithm using the Normalized Euclidean Distance (NormDist) method is measured.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.6 no.4
• /
• pp.269-278
• /
• 2004

Recently, critical velocity has become a topic to attract most interests from the researchers in the field of tunnel safety. As the minimum velocity to prevent smoke backlayering during a fire, many equations have been proposed so far, and the following three equations are being considered as a standard method in Korea to calculate the capacity of smoke extraction fans. Equation by Kennedy based on Froude number, Tetzner' s equation with additional variable, ${\beta}$ to modify the Kennedy's equation, and the equation with the concept of super critical velocity by Wu are studied in this paper for the comparative purpose. A contour map describing the relationship between the critical velocity and the capacity of smoke extraction fans is proposed as a tool to calculate the number of jet fans for smoke control during a fire in the local tunnels.

• Journal of Digital Convergence
• /
• v.12 no.6
• /
• pp.231-236
• /
• 2014

In this paper, we propose a processing speed improvement by adding a parallel processing based on device(graphic card) into a road region extraction by host(PC) based serial processing. The OpenCV CUDA supports the many functions of parallel processing method by interworking a conventional OpenCV with CUDA. Also, when interworking the OpenCV and CUDA, OpenCV functions completed a configuration are optimized the User's device(Graphic Card) specifications. Thus, OpenCV CUDA usage provides an algorithm verification and easiness of simulation result deduction. The proposed method is verified that the proposed method has a about 3.09 times faster processing speed than a conventional method by using OpenCV CUDA and graphic card of NVIDIA GeForce GTX 560 Ti model through experimentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.1
• /
• pp.11-19
• /
• 2016

Recently, global companies are developing the automobile technologies, converged with state-of-the-art IT technologies for the commercialization of autonomous vehicles. These autonomous vehicles are required the accurate lane information to enhance its reliability by controlling the vehicles safely. Hence, the study planned to examine possibilities of applying UAV photogrammetry of high-resolution images, obtained from the low altitudes. The high-resolution DSM and the ortho-images were generated from the GSD 7cm-level digital images that were obtained and based on the generated data, when the positions information of the roads including the lanes were extracted. In fact, the RMSE of verifying the extracted data was shown to be about 15cm. Through the results from the study, it could be concluded that the low alititude UAV photogrammetry can be applied for generating and updating a high-accuracy map of road areas.

• Journal of Korean Society for Geospatial Information Science
• /
• v.16 no.1
• /
• pp.49-55
• /
• 2008

The face extraction is very important to provide the images of the roads and road sides without the problem of privacy. For face extraction form roadside images, we detected the skin color area by using HSI and YCrCb color models. Efficient skin color detection was achieved by using these two models. We used a connectivity and intensity difference for grouping, skin color regions further we applied shape conditions (rate, area, number and oval condition) and determined face candidate regions. We applied thresholds to region, and determined the region as the face if black part was over 5% of the whole regions. As the result of the experiment 28 faces has been extracted among 38 faces had problem of privacy. The reasons which the face was not extracted were the effect of shadow of the face, and the background objects. Also objects with the color similar to the face were falsely extracted. For improvement, we need to adjust the threshold.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2291-2297
• /
• 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 Korean Tunnelling and Underground Space Association
• /
• v.22 no.4
• /
• pp.347-365
• /
• 2020

In order to resolve traffic problems in urban areas and to increase the area of green spaces, tunnels in downtown areas are being increased. Additionally, the application of large port smoke extraction ventilation systems is increasing as a countermeasure to smoke extraction ventilation for tunnels with high potential for traffic congestion. It is known that the smoke extraction performance of the large port smoke extraction system is influenced not only by the amount of the extraction flow rate, but also by various factors such as the shape of the extraction port (damper) and the extraction air velocity through a damper. Therefore, in this study, the design standards and installation status of each country were investigated. When the extraction air flow rate was the same, the smoke extraction performance according to the size of the damper was numerically simulated in terms of smoke propagation distance, compared and evaluated, and the following results were obtained. As the cross-sectional area of the smoke damper increases, the extraction flow rate is concentrated in the damper close to the extraction fan, and the smoke extraction rate of the damper in downstream decreases, thereby increasing the smoke propagation distance on the downstream side. In order to prevent such a phenomenon, it is necessary to reduce the cross-sectional area of the smoke damper and increase the velocity of passing air through the damper so that the pressure loss passing through the damper increases, thereby reducing the non-uniformity of smoke extraction flow rate in the extraction section. In this analysis, it was found that when the interval distance of the extraction damper was 50 m, the air velocity passing through damper was 4.4 m/s or more, and when the interval distance of the extraction dampers was 100 m, the air velocity passing through damper was greater than 4.84 m/s, it was found to be advantageous to ensure smoke extraction performance.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.4
• /
• pp.65-73
• /
• 2018

Although the road construction in forest is increasing and there is a need for development ecological restoration on deforest area, no consideration has been given to individual trees in there. This study analyzed aerial photographs of deforest area before and after road construction for determining the degree of forest destruction by extracting individual trees. Study area was selected in the sites where are damaged by road construction in GongJu-si, YuSung-gu, and YeongDong-gun. The aerial photograph taken 1979 before construction is panchromatic image of 80cm in GSD (Ground Sample Distance) and other photograph taken 2016 after construction is multi-spectral image of 10cm in GSD. In order to minimize the difference of GSD, we conducted image re-sampling process for setting to same GSD for the two photographs. After that we carried out visual interpretation method for determining to change of individual tree. The result found that for GongJu-si of the number of individual tree was 1,014 in 1979 and 886 in 2016, which decreased by 128 (12.6%) and the average width of those decreased from 5.77m to 5.75m by 0.47%. In case of YoungDong-gun, the number of it was 761 in 1979 and 746 in 2016, which decreased by 2.0% and the average width of it decreased from 8.99mm to 8.90m by 1.1%. Lastly in case of YuSung-gu, the number of it was 1,578 in 1979 and 988 in 2016, which decreased by 37.4% and the average width of it decreased from 7.09m to 6.65m by 6.21%. these result imply that road construction causes destruction of forests. Since there are limitations such as errors due to researcher, it is necessary to construct a quantitative analysis method for the change of the deforest area. It is need to study the method of extracting individual tree in deforest area more accurately using high-resolution image of GSD 10cm or more as well. This study can be used as a basic data for the ecological restoration of the deforest area considering characteristics of individual tree such as height, diameter at breast height, and biomass.

• The KIPS Transactions:PartB
• /
• v.16B no.4
• /
• pp.257-262
• /
• 2009

A method of the region extraction and recognition of a speed sign in the real road environment is proposed. The region of speed sign is extracted by using color information and then numbers are segmented in the region. We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. In image sequences of the real road environment, a robust recognition results are achieved with speed signs at normal condition as well as inclined.

• Journal of Korean Society of Transportation
• /
• v.14 no.3
• /
• pp.45-59
• /
• 1996

The shortest path algorithm for route guidance is implicitly required not only to support geometrical variations of transportation network such as U-TURN or P-TURN but to efficiency search reasonable routes in searching mechanism. The purpose of this paper is to integrate such two requirements ; that is, to allow U-TURN and P-TURN possibilities and to cut down searching time in locating routes between two points (origin and destination) in networks. We also propose a new type of link searching algorithm which can solve the limitation of vine building algorithm at consecutively left-turn prohibited intersections. The test site is a block of Gangnam road network that has some left-turn prohibited and allowed U-TURN intersections. Four models have been identified to be comparatively analyzed in terms of searching efficiency. The Models are as follows : (i) Model 1 - Link Searching Dijkstra Algorithm without Searching Area Extraction (SAE) ; (ii) Model 2 - Link Searching Dijkstra Algorithm with SAE ; (iii) Model 3 - Link Searching Bidirectional Dijkstra Algorithm without SAE ; and (iv) Model 4 - Link Searching Bidirectional Dijkstra Algorithm with SAE. The results of comparative evaluation show that Model 4 can effectively find optimum path faster than any other models as expected. Some discussions and future research agenda have been presented in the light of dynamic route guidance application of the urban ATIS.