• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.71-79
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• 2017

Recently, Fire watching and dangerous substances monitoring system has been being developed to enhance various fire related security. It is generally assumed that fire flame extraction plays a very important role on this monitoring system. In this study, we propose the fire flame extraction method of Non-Residential Facilities based on core object extraction in image. A core object is defined as a comparatively large object at center of the image. First of all, an input image and its decreased resolution image are segmented. Segmented regions are classified as the outer or the inner region. The outer region is adjacent to boundaries of the image and the rest is not. Then core object regions and core background regions are selected from the inner region and the outer region, respectively. Core object regions are the representative regions for the object and are selected by using the information about the region size and location. Each inner region is classified into foreground or background region by comparing its values of a color histogram intersection of the inner region against the core object region and the core background region. Finally, the extracted core object region is determined as fire flame object in the image. Through experiments, we find that to provide a basic measures can respond effectively and quickly to fire in non-residential facilities.

• Journal of Platform Technology
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• v.11 no.3
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• pp.24-31
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• 2023

Recently, interest in UAM (Urban Air Mobility, UAM), which can take off and land vertically in the operation of urban air transportation systems, has been increasing. Therefore, various start-up companies are developing related technologies as eco-friendly future transportation with advanced technology. However, studies on ways to increase safety in the operation of UAM are still insignificant. In particular, efforts are more urgent to improve the safety of risks generated in the process of attempting to land in the city center by UAM equipped with autonomous driving. Accordingly, this study proposes a plan to safely land by avoiding dangerous region that interfere when autonomous UAM attempts to land in the city center. To this end, first, the latitude and longitude coordinate values of dangerous objects observed by the sense of the UAM are calculated. Based on this, we proposed to convert the coordinates of the distorted planar image from the 3D image to latitude and longitude and then use the calculated latitude and longitude to compare the pre-learned feature descriptor with the HOG (Histogram of Oriented Gradients, HOG) feature descriptor to extract the dangerous Region. Although the dangerous region could not be completely extracted, generally satisfactory results were obtained. Accordingly, the proposed research method reduces the enormous cost of selecting a take-off and landing site for UAM equipped with autonomous driving technology and contribute to basic measures to reduce risk increase safety when attempting to land in complex environments such as urban areas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.374-380
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• 2019

Containers are fitted with various placards on the surface to indicate the risk of cargo. If the containers are loaded with dangerous goods, care should be taken in handling the containers. Therefore, as part of the port automation system, there is a demand for automatic placard recognition. In this paper, proposed is a method to extract placard areas from a container image, which is the first part of the placard recognition system. The fact that placards are of various types but all have a diamond shape can be an advantage in recognition. However, it is a disadvantage in recognition that the placards can be distorted in various ways because the container surface is not flat. When the proposed method was applied to actual images, type I error did not occur. In addition, since the shape feature of the object and basic image operations are used to extract regions of interest, it can be applied to various shape-based region extraction problems.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.29-36
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• 2021

Recently, due to climate change, the slope is increasing, and the risk of steep slope disasters such as the occurrence of slope collapse in the east coast and Busan region in 2019 and the Gokseong landslide in 2020 is increasing. Particularly, most national parks are made up of mountainous areas, and the risk of disasters on steep slopes is increasing. As the ground of the national park is aging and the weathering and jointing of the bedrock are accelerating due to climate change, the slope collapse and rockfall are increasing, and the annual number of visitors is increasing, it is necessary to manage steep slopes adjacent to multi-use facilities with many users. In this study, dangerous steep slopes that affect multi-use facilities in national parks were analyzed using GIS and verified through field surveys. As a process for extracting steep slopes adjacent to multi-use facilities in national parks, the slope was made in DEM and slopes of 34 degrees or higher were extracted. The difference between the maximum and minimum heights of the extracted slopes was used to confirm that the slopes met the standard for steep slopes, and the analysis of the slope direction was used to confirm whether it had an effect on the multi-use facilities. After that, precision aerial images and field photos were analyzed to finally identify risks at 4 sites, and field surveys were conducted. As a result of the field survey, all 4 sites were found to be steep slopes, 3 were graded D and 1 was graded C, so it was confirmed that management was required as a risk of collapse. All steep slopes extracted through GIS were found to be dangerous, so it is judged that the extraction of steep slopes through GIS would be appropriate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.659-665
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• 2019

Various placards are attached to the surface of a container depending on the risk of the cargo loaded. Containers with dangerous goods should be managed separately from ordinary containers. Therefore, as part of the port automation system, there is a demand for automatic recognition of placards. In this paper, proposed is a system that automatically extracts the placard area based on the shape features of the placard and recognizes the contents in it. Various distortions can be caused by the surface curvature of the container, therefore, attention should be paid to the area extraction and recognition process. The proposed system can automatically extract the region of interest and recognize the placard using the feature that the placard is diamond shaped and the class number is written just above the lower vertex. When the proposed system is applied to real images, the placard can be recognized without error, and the used techniques can be applied to various image analysis systems.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1520-1520
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• 2001

Food adulteration is a serious consumer fraud and a potentially dangerous practice. Regulatory authorities and food processors require a rapid, non-destructive test to accurately confirm authenticity in a range of food products and raw materials. Olive oil is prime target for adulteration either on the basis of the processing treatments used for its extraction (extra virgin vs virgin vs ordinary oil) or its geographical origin (e.g. Greek vs Italian vs Spanish). As part of an investigation into this problem, some preliminary work focused on the ability of near infrared spectroscopy to discriminate between virgin olive oils from separate regions of the Mediterranean i. e. Crete and the Peloponese. A total of 46 oils were collected: 18 originated in Crete and 28 in the Peloponese. Oils were stored in a temperature-controlled room at 2$0^{\circ}C$ prior to spectral collection at room temperature (15-18$^{\circ}C$). Samples (approximately 0.5$m\ell$) were placed in the centre of the quartz window in a camlock reflectance cell; the gold-plated baking plate was then gently placed into the cell against the glass so as to minimize the formation of air bubbles. The rear of the camlock cell was then screwed into place producing a sample thickness of 0.5mm. Spectra were recorded between 400 and 2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. Spectral collection took place over 2-3 days. Data were analysed using both WINISI and The Unscrambler software to investigate the possibility of discriminating between the oils from Crete and the Peloponese. A number of data pre-treatments were used and discriminant models were developed using discriminant PLS (WINISI & Unscrambler) and SIMCA (Unscrambler). Despite the small number of samples involved, a satisfactory discrimination between these two oil types was achieved. Graphical examination of principal component scores for each oil type also holds out the possibility of separating oils from either Crete and the Peloponese on the basis of districts within each region. These preliminary data suggest the potential of near infrared spectroscopy to act as a screening technique for the confirmation of geographic origin of extra virgin olive oils. The sample presentation strategy adopted uses only small volumes of material and produces high quality spectra.