• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.53-63
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• 1999

For the close range digital photogrammetry, multi-step procedures should be embodied in an integrated system. However, it is hard to construct an Integrated system through conventional procedural processing. Using Object Oriented Programming(OOP), photogrammetric processings can be classified with corresponding subjects and it is easy to construct an integrated system lot digital photogrammetry as well as to add the newly developed classes. In this study, the equation of 3-dimensional mathematic model is developed to make an immediate calibration of the CCD camera, the focus distance of which varies according to the distance of the object. Classes for the input and output of images are also generated to carry out the close range digital photogrammetric procedures by OOP. Image matching, coordinate transformation, dirct linear transformation and bundle adjustment are performed by producing classes corresponding to each part of data processing. The bundle adjustment, which adds the principle coordinate and focal length term to the non-photogrammetric CCD camera, is found to increase usability of the CCD camera and the accuracy of object positioning. In conclusion, classes and their hierarchies in the digital photogrammetry are designed to manage multi-step procedures using OOP and close range digital photogrammetric process is implemented using CCD camera in an integrated System.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.17-26
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• 1998

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But for the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. The time-of-flight(TOF) method generally used for distance measurement can not distinguish small object patterns of plane, corner or edge. To resolve the problem, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensors has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. Also simple patterns are classified based on analyzing signal reflections. In this paper we propose a method of a sensor array system with improved capability in pattern distinction using electronic circuits accompanying the sensor array, and intelligent algorithm based on neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. A set of different return signals from neighborhood sensors is manipulated to provide enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

• Journal of Sensor Science and Technology
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• v.11 no.2
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• pp.84-92
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• 2002

A $32{\times}32$ pixels foveated (linear-polar) structure retina chip with the function of local-light adaptation for edge detection has been designed and fabricated using CMOS technology. Human retina can detect a wide range of light intensity. In this study, we use the biologically-inspired visual signal processing mechanism that consists of photoreceptors, horizontal cells, and bipolar cells in order to implement the function of edge detection in the retina chip. For a local-light adaptive function, the size of receptive field is changed locally according to the input light intensity. The spatial distribution of sensing pixels in the foveated retina chip has the advantages of selective reduction of image data and good resolution in central part to carry out the elaborate image processing with still enough resolution in the outer parts. The designed chip has been fabricated using standard $0.6\;{\mu}m$ double-poly triple-metal CMOS technology and optimized using HSPICE simulator.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.95-102
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• 2003

In surveillance video system, there are many classes of images and some spatial regions are more important than other regions. The conventional compression method in this system have been compressed there full frames without classfying them depend on their important parts. To improve the accuracy of the image coding and deliver effective compression for the surveillance video system, it was necessary to separate the regions according to their importance. In this paper, we propose a new effective surveillance video image compression method. The proposed scheme defines importance based three-level region of interest block in a frame, such as background, motion object block, and the feature object block. A captured video image frame can be separated to these three different levels of block regions. And depends on the priority, each block can be modified and compressed in different resolution, compression ratio and qualify factor. Therefore, in surveillance video system, this algorithm not only reduces the image processing time and space, but also guarantees the Important image data in high quality to acquire the system's goal.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.315-324
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• 2023

A simple and accurate whole body rehabilitation interaction technology using immersive digital content is needed for elderly patients with steadily increasing age-related diseases. In this study, we introduce whole-body interaction technology using HoloLens and Kinect for this purpose. To achieve this, we propose three coordinate transformation methods: mesh feature point-based transformation, AR marker-based transformation, and body recognition-based transformation. The mesh feature point-based transformation aligns the coordinate system by designating three feature points on the spatial mesh and using a transform matrix. This method requires manual work and has lower usability, but has relatively high accuracy of 8.5mm. The AR marker-based method uses AR and QR markers recognized by HoloLens and Kinect simultaneously to achieve a compliant accuracy of 11.2mm. The body recognition-based transformation aligns the coordinate system by using the position of the head or HMD recognized by both devices and the position of both hands or controllers. This method has lower accuracy, but does not require additional tools or manual work, making it more user-friendly. Additionally, we reduced the error by more than 10% using RANSAC as a post-processing technique. These three methods can be selectively applied depending on the usability and accuracy required for the content. In this study, we validated this technology by applying it to the "Thunder Punch" and rehabilitation therapy content.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Environmental Science International
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• v.22 no.11
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• pp.1389-1402
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• 2013

This paper focuses on the impacts of waste dumping on inorganic nutrients in the dumping area of the Yellow Sea, and the effect of an governmental regulation of pollution in dumping areas. The environmental variables and parameters of the dumping and reference areas in the Yellow Sea were measured during July 2009 and analyzed. In addition, the analyzed data for inorganic nutrients over the last 10 years were obtained from the Korea Coast Guard (KCG) and the National Fisheries Research and Development Institute (NFRDI). The chemical environment of the study area revealed increases in concentrations of inorganic nutrients, Chemical Oxygen Demand (COD), and Volatile Suspended Solids (VSS) in the bottom layer. On the contrary, the pH level was decreased. Most notably, the time series data of inorganic nutrients showed gradual increase over time in the dumping area, and thus, the oligotrophic waters trend toward eutrophic waters. The increases appears to be due to the disposal of large amounts of organic waste. In recent times, the wastes disposed at the area were largely comprised of livestock wastewater, and food processing waste water. The liquefied waste, which contains an abundance of nutrients, causes a sharp increase in concentrations of inorganic nitrogen in the dumping area. On the one hand, the dumping sites have been deteriorated to such an extent that pollution has become a social problem. Consequentially, the government had a regulatory policy for improvement of marine environmental since 2007 in the dumping area. Hence, the quality of marine water in the dumping site has improved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.505-513
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• 2014

The RapidEye can acquire the 6.5m spatial resolution satellite imagery with the high temporal resolution on each day, based on its constellation of five satellites. The image products are available in two processing levels of Basic 1B and Ortho 3A. The Basic 1B image have radiometric and sensor corrections and include RPCs (Rational Polynomial Coefficients) data. In Korea, the geometric accuracy of RapidEye imagery can be improved, based on the scaled national digital maps that had been built. In this paper, we present the fully automated procedures to georegister the 1B data using 1:25,000 digital maps. Those layers of map are selected if the layers appear well in the RapidEye image, and then the selected layers are RPCs-projected into the RapidEye 1B space for generating vector images. The automated edge-based matching between the vector image and RapidEye improves the accuracy of RPCs. The experimental results showed the accuracy improvement from 2.8 to 0.8 pixels in RMSE when compared to the maps.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.73-85
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• 2006

Array observations of the vertical component of microtremors are frequently conducted to estimate a subsurface layered-earth structure on the assumption that microtremors consist predominantly of the fundamental mode Rayleigh waves. As a useful tool in the data collection, processing and analysis, the spatial autocorrelation (SPAC) method is widely used, which in practice requires a circle array consisting of M circumferential stations and one centre station (called "M-station circle array", where M is the number of stations). The present paper considers the minimum number of stations required for a circle array for efficient data collection in terms of analytical efficacy and field effort. This study first rearranges the theoretical background of the SPAC algorithm, in which the SPAC coefficient for a circle array with M infinite is solely expressed as the Bessel function, $J_0(rk)$ (r is the radius and k the wavenumber). Secondly, the SPAC coefficient including error terms independent of the microtremor energy field for an M-station circle array is analytically derived within a constraint for the wave direction across the array, and is numerically evaluated in respect of these error terms. The main results of the evaluation are: 1) that the 3-station circle array when compared with other 4-, 5-, and 9-station arrays is the most efficient and favourable for observation of microtremors if the SPAC coefficients are used up to a frequency at which the coefficient takes the first minimum value, and 2) that the Nyquist wavenumber is the most influential factor that determines the upper limit of the frequency range up to which the valid SPAC coefficient can be estimated.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.47-54
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• 2017

Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.