• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.971-976
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• 2021

In this paper, we design a facial facial image data collection system for heart rate measurement using a web camera. The design content of this paper is a function of collecting user face image information using a web camera and measuring heart rate using the user's face image information. There is a possibility that an error may occur due to non-contact heart rate measurement using a web camera. Therefore, in this paper, it is to be used for correcting heart rate program errors through classification of data in cases of error and normal. The data in case of error can be used for the purpose of reducing the error. Experiments were conducted on the proposed ideas and designed in this paper. As a result of the experiment, it was confirmed that it operates normally.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1085-1095
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• 2023

Time-series data generated from satellite data are crucial resources for change detection and monitoring across various fields. Existing research in time-series data generation primarily relies on single-image analysis to maintain data uniformity, with ongoing efforts to enhance spatial and temporal resolutions by utilizing diverse image sources. Despite the emphasized significance of time-series data, there is a notable absence of automated data collection and preprocessing for research purposes. In this paper, to address this limitation, we propose a system that automates the collection of satellite information in user-specified areas to generate time-series data. This research aims to collect data from various satellite sources in a specific region and convert them into time-series data, developing an automatic satellite image collection system for this purpose. By utilizing this system, users can collect and extract data for their specific regions of interest, making the data immediately usable. Experimental results have shown the feasibility of automatically acquiring freely available Landsat and Sentinel images from the web and incorporating manually inputted high-resolution satellite images. Comparisons between automatically collected and edited images based on high-resolution satellite data demonstrated minimal discrepancies, with no significant errors in the generated output.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.124-129
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• 2021

As the 4th industrial era is in full swing, the public's interest in related technologies such as artificial intelligence, big data, and block chain is increasing. As artificial intelligence technology is used in various industrial fields, the need for research methods incorporating artificial intelligence technology in related fields is also increasing. Evidence collection among digital forensic investigation techniques is a very important procedure in the investigation process that needs to prove a specific person's suspicions. However, there may be cases in which evidence is damaged due to intentional damage to evidence or other physical reasons, and there is a limit to the collection of evidence in this situation. Therefore, this paper we intends to propose an artificial intelligence-based evidence collection system that analyzes numerous image files reported by citizens in real time to visually check the location, user information, and shooting time of the image files. When this system is applied, it is expected that the evidence expected data collected in real time can be actually used as evidence, and it is also expected that the risk area analysis will be possible through big data analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.129-136
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• 2012

In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.534-542
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• 2001

Recent content-based image retrieval systems make use of a local single server contained a limited number of images. So these systems are not satisfactory for the Web user's needs that make request for various images on the Web. A content-based image retrieval system that has regard for a great number of Web images has to stand on the basis of real-time first of all. Therefore, to implement the above system we have to resolve a problem of large waste time to take for an image collection and feature extractions. In recent, PC clusters with a load distribution are implemented for the purpose of high-performance data processing. In this paper, we decreased the whole retrieval time by distributing the tasks of image collection and feature extraction to take much time among the slave computers of the PC cluster, and so we found the possibility of the real-time processing in the retrieval of Web images.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.23-30
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• 2020

The use of increased computing power, machine learning, and deep learning techniques have dramatically increased in various sectors. In particular, image detection algorithms are broadly used in forestry and remote sensing areas to identify forest types and tree species. However, in South Korea, machine learning has rarely, if ever, been applied in forestry image detection, especially to classify tree species. This study integrates the application of machine learning and forest image detection; specifically, we compared the ability of two machine learning data collection methods, namely image data captured by forest experts (D1) and web-crawling (D2), to automate the classification of five trees species. In addition, two methods of characterization to train/test the system were investigated. The results indicated a significant difference in classification accuracy between D1 and D2: the classification accuracy of D1 was higher than that of D2. In order to increase the classification accuracy of D2, additional data filtering techniques were required to reduce the noise of uncensored image data.

• Journal of the Korean Society of Costume
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• v.65 no.4
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• pp.76-90
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• 2015

Based on a concept of Nietzschean nihilism, this study aimed at interpreting the nihilism in arts and its expressions, also analyzing the modern fashion collection from the same angle. The research was centered on arts after 1980, when post-modern formal destruction expanded in earnest and on the fashion collection after the 20th century, easily accessible to data. Particularly, it set 1994 nihilism collection by Alexander McQueen, a representative nihilist fashion designer as a starting point. Nietzsche mentioned that true arts may be achieved when Apollonian characteristics including a bodily sensory system and an idealization process and Dionysian characteristics including every human feeling are integrated. Besides, he emphasized the importance of an artist being represented as an image of ${\ddot{U}}bermensch$. The ${\ddot{U}}bermensch$ image, reflected in arts and artistic nihilism, represents themes of violence/death, realistic/unrealistic expressions, human body/inhuman aversion materials and the transmutation of a form. Fashion collection expressions, owing to the special characteristic of the show form unlike other arts, were segmented as a realistic ${\ddot{U}}bermensch$ image using a model in a theme, expression, material and form. The theme of violence/death was divided into the death of human and a society. Human life/death was expressed as destruction of human weakness and self-identity, sexual objectification and violence, and social death as destruction and conflict of a class, nation, culture and nature. As for the expression, it was divided into the realistic expression of the primitive/natural and directing of an unrealistic atmosphere using a show.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.97-116
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• 1994

Today advanced traffic management systems are required because of a high increase in traffic demand. Accordingly, the objective of this study is to take advantage of image processing systems and present image processing methods available for collection of the data on traffic characteristics, and then to investigate the possibility of traffic flow analysis by means of comparison and analysis of measured traffic flow. Data were collected at two places of Daegu city and Kyongbu expressway by using VTR. Rear view (down stream) and frontal view (up stream) methods were employed to compare and analyze traffic characteristics including traffic volume, speed, time-headway, time-occupancy, and vehicle-length, by analysis of measured traffic flow and image processing respectively. Judging from the results obtained by this study, image processing techniques are sufficient for the analysis of traffic volume, but a frame grabber equipped with high speed processor is necessary as well, with low level system judged to be sufficient for traffic volume analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.195-200
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• 2013

This paper proposes an SNS and Web Data Analytics System which can utilize a business marketing strategy by analyzing negative SNS and Web Data that can do great damage to a business image. It consists of the Data Collection Module collecting SNS and Web Data, the Hbase Module storing the collected data, the Data Analysis Module estimating and classifying the meaning of data after an semantic analysis of the collected data, and the PHS Module accomplishing an optimized Map Reduce by using SNS and Web data involved a Businesse. This paper can utilize this analysis result for a business marketing strategy by efficiently managing SNS and Web data with these modules.