• Journal of KIBIM
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• v.11 no.2
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• pp.54-59
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• 2021

In the process of designing a building, the process of expressing the designer's ideas through images is essential. However, it is expensive and time consuming for a designer to analyze every individual case image to generate a hypothetical design. This study aims to visualize the basic design draft sketch made by the designer as a real image using the Generative Adversarial Network (GAN) based on the continuously accumulated architectural case images. Through this, we proposed a method to build an automated visualization environment using artificial intelligence and to visualize the architectural idea conceived by the designer in the architectural planning stage faster and cheaper than in the past. This study was conducted using approximately 20,000 images. In our study, the GAN algorithm allowed us to represent primary materials and shades within 2 seconds, but lacked accuracy in material and shading representation. We plan to add image data in the future to address this in a follow-up study.

• Journal of the Korean Professional Engineers Association
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• v.38 no.1
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• pp.52-54
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• 2005

Korean metropolises are choked by lack of green space to attain the limit of horizontal expansion. The alternative plan is trying total expansion that the green zone and road are made from the rest site by high-rise buildings. And high-rise building can solve indiscriminate development to attain the limit situation. The building of landmark can be the image of the nation and the pride of the citizen. The relaxing the height restriction of government can be whole nation's interests. Appearing high-rise building in overpopulated city is the subject of a generation and this trend cannot be avoided.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.31-39
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• 2007

As the availability of images from airborne digital camera with high resolution is expanded, a lot of concern are shown about the production of orthoimage and digital map. This study presents the method of updating digital map using orthoimage from airborne digital camera image. Images were georectified using GPS surveying data. For the generation of orthoimage, Lidar DEM was used. The absolute positional accuracy of orthoimage was evaluated using GPS surveying data. And that of the building layer of digital map was estimated using the existed digital map at the scale of 1:1,000. The absolute positional accuracy of orthoimage was as followed: RMSE in X and Y were ${\pm}0.076m$ and ${\pm}0.294m$. The RMSE of the building layer were ${\pm}0.250m$ and ${\pm}0.210m$ in X and Y directions, respectively. The RMSE of the digital map using orthoimage from Aerial Digital Camera image fell within allowable error range established by NGII. Consequently, updating digital map using orthoimage from Aerial Digital Camera image can be applied to various fields including the construction of the framework data and the GIS of local government.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.1-9
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• 2000

In the recent day, the necessity and the effective usage are increased rapidly, and it is applied in many other fields as well as in the field of ortho-photo map. In this study, we extract each objects on the aerial image and automatically classify graphic information to produce digital map using only digital ortho-image without particular drawing devices for producing digital map. For this purpose, we have applied a lot of the image processing techniques and fuzzy theory, classified outline and lane of road and building, and had each layer according to each feature. Especially, in the case of the building, the outer vector lines extracted by pixel unit at the building were very complex, but we have developed the program to be expressed by I-dimensional linear type between building corners. In the result of this study, we could not extract and recognize all of the object on the image all together, but we have got the error within 50cm using semi-automatic technique. Therefore, this method will be used effectively in producing 1/5,000 digital map.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1025-1034
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• 2022

In this paper, we propose a post-processing method through interpolation of hole regions that occur when extracting point clouds. When image matching is performed on stereo image data, holes occur due to occlusion and building façade area. This area may become an obstacle to the creation of additional products based on the point cloud in the future, so an effective processing technique is required. First, an initial point cloud is extracted based on the disparity map generated by applying stereo image matching. We transform the point cloud into a grid. Then a hole area is extracted due to occlusion and building façade area. By repeating the process of creating Triangulated Irregular Network (TIN) triangle in the hall area and processing the inner value of the triangle as the minimum height value of the area, it is possible to perform interpolation without awkwardness between the building and the ground surface around the building. A new point cloud is created by adding the location information corresponding to the interpolated area from the grid data as a point. To minimize the addition of unnecessary points during the interpolation process, the interpolated data to an area outside the initial point cloud area was not processed. The RGB brightness value applied to the interpolated point cloud was processed by setting the image with the closest pixel distance to the shooting center among the stereo images used for matching. It was confirmed that the shielded area generated after generating the point cloud of the target area was effectively processed through the proposed technique.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• Journal of IKEEE
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• v.16 no.2
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• pp.95-101
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• 2012

A novel approach for the reconstruction of 3D building model from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is proposed for connecting low-level linear structures. After the straight lines are extracted from an edge image using the CNN, rectangular boundaries are then found by using an edge-based grouping approach. In order to avoid producing unrealistic building models from grouping lined segments, a hierarchical grouping method is proposed in this paper. The proposed hierarchical grouping method is evaluated with a set of aerial image data in the experiment. The results show that the proposed method can be successfully applied for the reconstruction of 3D building model from satellite images.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.69-79
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• 2023

In this study, an experimental study was conducted on the development of crack monitoring technology in buildings using a mechanochromic sensor. After attaching a mechanochromic sensor to the cracks induced in the concrete specimen, the color variation image of the sensor according to the progress of the cracks was taken. In addition, a method of analyzing a sensor color variation image was proposed, and an equation for deriving a crack's width from the relationship between the analysis result and the crack width was also proposed. In addition, the possibility of using an mechanochromic sensor for monitoring cracks in buildings was confirmed through the verification of crack width monitoring technology.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.151-159
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• 2013

The building information should be up-to-date information and propagated rapidly for urban modeling, terrain analysis, life information, navigational system, and location-based services(LBS), hence the most recent and updated data of the building information have been required of researchers. This paper presents the developed system to extract the 3-dimension spatial information from aerial orthoimage and LiDAR data of HSI color model. In particular, this paper presents the image processing algorithm to extract the outline of specific buildings and generate the building polygon from the image using HIS color model, recursive backtracking algorithm and the search maze algorithm. Also, this paper shows the effectivity of the HIS color model in the image segmentation.