• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.429-438
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• 2021

In recent, realistic content has been applied in various ways due to the development of display technology and hologram, the final realistic content technology, have been used limitedly in accordance with the growing public demand. However, most realistic content requires additional devices of HMD (head mounted device) or glasses type, and other realistic content display technologies deliver a single image plane in the experience space to the user, providing a monotonous content experience. Various realistic contents with hologram technology are introduced in this work. In addition, we propose an interaction based realistic hologram service based that combines projection mapping and floating holograms. Projection-mapped screens and multi-floating hologram device provide a three-dimensional volumetric space with extended depth orientation from the user's point of view, while allowing users' entire and partial motions to be recognizable through multiple sensors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.91-103
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• 2006

This paper proposes a methodology to evaluate the quality and level of difficulty of fingerprint image databases, which leads to objective evaluation for the performance of fingerprint recognition system. Influencing factors to fingerprint matching are defined and the matching performance between two fingerprint images is evaluated using segmentation and orientation filed. In this study, a hierarchical processing method is proposed to measure an orientation field, which is able to improve the matching speed and accuracy. The results of experiments demonstrate that the defined influencing factors can describe the characteristics of fingerprint databases. Level of difficulty for fingerprint databases enables the performance of fingerprint recognition algorithms to be evaluated and compared even with different databases.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.47-62
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• 2016

An integrated database(DB) system was developed to manage the marine geological data and geophysical data acquired from around the Korean peninsula from 2009 to 2013. Geological data such as size analysis data, columnar section images, X-ray images, heavy metal data, and organic carbon data of sediment samples, were collected in the form of text files, excel files, PDF files and image files. Geophysical data such as seismic data, magnetic data, and gravity data were gathered in the form of SEG-Y binary files, image files and text files. We collected scientific data from research projects funded by the Ministry of Oceans and Fisheries, data produced by domestic marine organizations, and public data provided by foreign organizations. All the collected data were validated manually and stored in the archive DB according to data processing procedures. A geographic information system was developed to manage the spatial information and provide data effectively using the map interface. Geographic information system(GIS) software was used to import the position data from text files, manipulate spatial data, and produce shape files. A GIS DB was set up using the Oracle database system and ArcGIS spatial data engine. A client/server GIS application was developed to support data search, data provision, and visualization of scientific data. It provided complex search functions and on-the-fly visualization using ChartFX and specially developed programs. The system is currently being maintained and newly collected data is added to the DB system every year.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.154-162
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• 2021

The naturally opened Han river estuary is a place where the flows of the Han river, Imjin river, Yaesung river meet with West Sea of Korea, so the hydrodynamic mechanism(Impact-Response) structure of Han river estuary is complex. Continuous observation and measurement due to the morphological characteristics at the estuary are required to maintain the estuary environment and river management facilities. However, the Sannam wetland(the study area) is in the military operation area. Therefore, Sannam wetland has the limited access under the control from military office. In 2020, there had a natural disaster due to flooding in August and COVID-19, and it made a survey hard. The noncontact survey technique, the analysis of LANDSAT images at Sannam wetland, was applied to analyze riverbed fluctuation and morphological transformation around Sannam wetland. LANDSAT images obtained from EarthExplorer, USGS and analyzed by QGIS. The analysis was performed based on the area and the distance near Sannam wetland. As a result, an erosion was happened on the downstream of the study area, and the upstream of the study area did not have any serious sediment transport. Considering the resolution of LANDSAT images, this noncontect survey technique is applicable to manage the study area. From the analysis of LANDSAT images, it is assumed that the tidal effect is greater than the inflow from the upstream. The pattern change of tidal response causes the damage of the river facilities near the Hangang river estuary.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.117-126
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• 2022

Currently, the number of bridge structures in Korea is continuously increasing and enlarged, and the number of old bridges that have been in service for more than 30 years is also steadily increasing. Bridge aging is being treated as a serious social problem not only in Korea but also around the world, and the existing manpower-centered inspection method is revealing its limitations. Recently, various bridge damage detection studies using deep learning-based image processing algorithms have been conducted, but due to the limitations of the bridge damage data set, most of the bridge damage detection studies are mainly limited to one type of crack, which is also based on a close set classification model. As a detection method, when applied to an actual bridge image, a serious misrecognition problem may occur due to input images of an unknown class such as a background or other objects. In this study, five types of bridge damage including crack were defined and a data set was built, trained as a deep learning model, and an open set recognition-based bridge multiple damage recognition model applied with OpenMax algorithm was constructed. And after performing classification and recognition performance evaluation on the open set including untrained images, the results were analyzed.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.63-75
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• 2016

Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.