• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.263-271
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• 2016

Localizing an object in image is a common task in the field of computer vision. As the existing methods provide a detection for the single object in an image, they have an utilization limit for the use of the application, due to similar objects are in the actual picture. This paper proposes an efficient method of object localization for image recognition. The new proposed method uses color correlation back-projection in the YCbCr chromaticity color space to deal with the object localization problem. Using the proposed algorithm enables users to detect and locate primary location of object within the image, as well as candidate regions can be detected accurately without any information about object counts. To evaluate performance of the proposed algorithm, we estimate success rate of locating object with common used image database. Experimental results reveal that improvement of 21% success ratio was observed. This study builds on spatially localized color features and correlation-based localization, and the main contribution of this paper is that a different way of using correlogram is applied in object localization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.87-94
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• 2019

Recently, the advance of accurate dynamic displacement measurement devices, such as GPS, computer vision, and optic laser sensor, has enhanced the structural monitoring technology. In this study, the dynamic displacement data was used to verify the applicability of the structural physical parameter estimation method through subspace system identification. The subspace system identification theory for estimating state-space model from measured data and physics-based interpretation for deriving the physical parameter of the estimated system are presented. Three-degree-freedom steel structures were fabricated for the experimental verification of the theory in this study. Laser displacement sensor and accelerometer were used to measure the displacement data of each floor and the acceleration data of the shaking table. Discrete state-space model generated from measured data was verified for precision. The discrete state-space model generated from the measured data extracted the floor stiffness of the building after accuracy verification. In addition, based on the story stiffness extracted from the state space model, five column stiffening and damage samples were set up to extract the change rate of story stiffness for each sample. As a result, in case of reinforcement and damage under the same condition, the stiffness change showed a high matching rate.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.631-640
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• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• The Korean Journal of Physiology and Pharmacology
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• v.19 no.2
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• pp.167-175
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• 2015

A retinal prosthesis is being developed for the restoration of vision in patients with retinitis pigmentosa (RP) and age-related macular degeneration (AMD). Determining optimal electrical stimulation parameters for the prosthesis is one of the most important elements for the development of a viable retinal prosthesis. Here, we investigated the effects of different charge-balanced biphasic pulses with regard to their effectiveness in evoking retinal ganglion cell (RGC) responses. Retinal degeneration (rd1) mice were used (n=17). From the ex-vivo retinal preparation, retinal patches were placed ganglion cell layer down onto an $8{\times}8$ multielectrode array (MEA) and RGC responses were recorded while applying electrical stimuli. For asymmetric pulses, 1st phase of the pulse is the same with symmetric pulse but the amplitude of 2nd phase of the pulse is less than $10{\mu}A$ and charge balanced condition is satisfied by lengthening the duration of the pulse. For intensities (or duration) modulation, duration (or amplitude) of the pulse was fixed to $500{\mu}s$($30{\mu}A$), changing the intensities (or duration) from 2 to $60{\mu}A$(60 to $1000{\mu}s$). RGCs were classified as response-positive when PSTH showed multiple (3~4) peaks within 400 ms post stimulus and the number of spikes was at least 30% more than that for the immediate pre-stimulus 400 ms period. RGC responses were well modulated both with anodic and cathodic phase-1st biphasic pulses. Cathodic phase-1st pulses produced significantly better modulation of RGC activity than anodic phase-1st pulses regardless of symmetry of the pulse.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.435-444
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• 2019

Recently, DL (Deep Learning) has been rapidly applied in various fields. In particular, classification and object recognition from images are major tasks in computer vision. Most of the DL utilizing imagery is primarily based on the CNN (Convolutional Neural Network) and improving performance of the DL model is main issue. While most CNNs are involve with images for training data, this paper aims to classify and recognize objects using DSM (Digital Surface Model), and slope and aspect information derived from the DSM instead of images. The DSM data sets used in the experiment were established by DGPF (German Society for Photogrammetry, Remote Sensing and Geoinformatics) and provided by ISPRS (International Society for Photogrammetry and Remote Sensing). The CNN-based SegNet model, that is evaluated as having excellent efficiency and performance, was used to train the data sets. In addition, this paper proposed a scheme for training data generation efficiently from the limited number of data. The results demonstrated DSM and derived data could be feasible for semantic classification with desirable accuracy using DL.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.701-709
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• 2008

Surface Image Velocimetry (SIV) is an instrument to measure water surface velocity by using image processing techniques. It gives us one of the easiest ways to measure water velocity. However, since it requires a set of plane survey data to estimate the velocity, it may give us some kind of misconcept that its usage would be difficult or cumbersome in spite of its handiness. If it has a feature that can estimate the plane survey data easily, it may be treated as like one of the conventional propeller velocimetries and its applicability would be improved so high. The present study is to propose a method to estimate the plane geometry of the physical coordinate with a calibrated camera. With the feature we can half-automatize the estimating procedure for the whole water velocity field. Photogrammetric technique to calculate the plane coordinates of the reference points with a calibrated camera was studied, which has originally studied for long time in the field of computer vision. By applying this technique to SIV, it is possible to estimate the location of reference coordinates for projective transform without plane survey. With this procedure the cumbersome plane survey for the reference points is omitted. One example application of the developed method showed fairly good results with insignificant errors.

• Archives of design research
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• v.17 no.2
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• pp.5-14
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• 2004

Introducing human capacities of control and sensation which have been overlooked into Human-Computer Interaction(HCI), Ubiquitous computing, Augmented Reality and others have been researched recently. New vision of HCI has embodied in Tangible User Interface(TUI). TUI allows users to grasp and manipulate bits with everyday physical object and architectural surface and also TUI enables user to be aware of background object at the periphery of human perception using ambient display media such of light, sound, airflow and water movement. Tangibles, physical object which constitutes TUI system, is the physical object embodied digital bit. Tangibles is not only input device but also the configuration of computing. To get feedback of computing result, user controls the system with Tangibles as action and the system represents reaction in response to User's action. User appreciates digital representation (sound, graphic information) and physical representation (form, size, location, direction etc.) for reaction. TUI's characters require the consideration about both user's action and system's reaction. Therefore we have to need the method to be concerned about physical object and interaction which can be combined with action, reaction and feedback.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.713-723
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• 2017

Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.495-503
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• 2014

As the number of vehicles has been sharply increases, the significance of safety and effective operation issues in the parking lot is being emphasized, which takes a part of the transportation system. Recently, there have been several studies for the parking management by detecting moving object, however, recognizing numbers of fast-moving vehicles simultaneously in the picture is still a challenging problem. The parking lot in public area, or large-sized buildings has clear parking section, whereas the sensor system is configured to monitor a plurality of parking spaces. Therefore, by considering those parking lots, we suggested to develop the real-time parking availability information system by applying the real-time image processing techniques. with the help of template matching. Following the study, we wanted to provide the alternative method for parking management system through the reference template makers by recognizing movements of parked vehicles with the size and shape, regardless of direct detecting of driving movements. In addition, we evaluated the applicability and performances of the information system, presented in this study, and implemented a prototype system to simulate the parking statuses of each floor. In fat, it was possible to manage and analyze statistics about the total number of parking spaces and the number of vehicles parked through real-time video flames. We expected that the result of the study will be advanced, following the user-friendliness and cost reduction in operating parking management system and giving information by efficient analysis of parking situation.