• 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 the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.10-18
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• 2010

This paper proposes an image stabilization algorithm for close watching UAV(Unmanned Aerial Vehicle) using motion separation and stabilization mode. The motion of UAV is composed of its actual navigating motion and unwanted vibrating motion so that image sequences obtained from UAV are shaken randomly. In order to stabilize these images we separate the vibrating motion component from UAV motion and remove the effect caused by it from image sequences. In the proposed algorithm the motion and global intensity change of two consecutive images are modeled with 6 motion parameters and 2 intensity change parameters respectively. These modeled parameters are estimated by non-linear least square method based on Gauss-Newton algorithm. The vibrating motion component is separated from the estimated motion using IIR filtering and the geometric deformation caused by it is removed from image sequences. In order to apply the proposed method to real aerial image sequences with many abrupt changes of camera view, we proposed a stabilizing method using two different modes named as stabilizing and non-stabilizing mode. Experimental results show that the accuracy of motion estimation is 99% and the efficiency of removing the vibrating motion component is 90%. We apply the proposed method to real aerial image sequences and verified its stabilizing performance.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.8
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• pp.62-71
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• 2001

This paper presents a design of the real-time digital image enhancement preprocessor for CMOS image sensor. CMOS image sensor offers various advantages while it provides lower-quality images than CCD does. In order to compensate for the physical limitation of CMOS sensor, the spatially adaptive contrast enhancement algorithm was incorporated into the preprocessor with color interpolation, gamma correction, and automatic exposure control. The efficient hardware architecture for the preprocessor is proposed and was simulated in VHDL. It is composed of about 19K logic gates, which is suitable for low-cost one-chip PC camera. The test system was implemented on Altera Flex EPF10KGC503-3 FPGA chip in real-time mode, and performed successfully.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.569-579
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• 2013

Robot control and image processing using a smartphone and Wi-Fi communication is introduced. The robot has a wheel and quadruped mechanism that is transformed according to the environment and is mainly used for drug bottle delivery. The captured image on the camera is transmitted to the smartphone in the form of stream data, and the image data is processed in the smartphone to enable the robot to identify an object and to control the robot itself. A network was constructed so that only image data from the stream data was used, and an image processing scheme to identify the drug bottle and deliver it to a person using a robot arm is also presented. In this study, image processing techniques and algorithms were purely implemented on a smartphone with considerable computational power and multiple functions rather than a computer, which contributes to the intelligence and miniaturization of the robot system.

• The Journal of the Petrological Society of Korea
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• v.11 no.2
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• pp.65-73
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• 2002

The wavy extinction of quartz grains can be used as a good indicator to show the degree of rock deformation. To determine degree of the rock deformation, intensity of wavy extinction (IWE) of quartz grains was measured by using polarizing microscope, digital camera, and NIH image (or Scion Image). In this experiment, the measurement was performed along the line perpendicular to the subgrain boundary of wavy extinction. IWE was measured when a quartz grain shows maximum extinction in polarizing microscope. NIH image was represented in terms of 256 gray-scale brightness, which was associated with intensity of the wavy extinction. IWE was determined by the degree of brightness versus the measuring length of a quartz grain. IWE was analysed in the distribution chart with the collection unit of 5. Regarding the characteristics of data distribution, the median between the mode and the median of the histogram is defined as a representative value for the IWE, and this value is subdivided into the five levels of rock deformation zones (lowest- or non-, low-, medium-, high-, and highest deformation) with their respective indices (D1, D2, D3, D4, and D5). The correlation between the Eonyang Granite and the Yangsan Fault was investigated by using the indices. The results indicate that IWE values decreased away from the fault.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.3
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• pp.11-19
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• 2009

Recently, concerns relating to the maintenance of large structures have been increased. In addition, the number of large structures that need to be evaluated for their structural safety due to natural disasters and structural deterioration has been rapidly increasing. It is common for the structural characteristics of an older large structure to differ from the characteristics in the initial design stage, and changes in dynamic characteristics may result from a reduction in stiffness due to cracks on the materials. The process of deterioration of such structures enables the detection of damaged locations, as well as a quantitative evaluation. One of the typical measuring instruments used for the monitoring of bridges and buildings is the dynamic measurement system. Conventional dynamic measurement systems require considerable cabling to facilitate a direct connection between sensor and DAQ logger. For this reason, a method of measuring structural responses from a remote distance without the mounted sensors is needed. In terms of non-contact methods that are applicable to dynamic response measurement, the methods using the doppler effect of a laser or a GPS are commonly used. However, such methods could not be generally applied to bridge structures because of their costs and inaccuracies. Alternatively, a method using a visual image can be economical as well as feasible for measuring vibration signals of inaccessible bridge structures and extracting their dynamic characteristics. Many studies have been conducted using camera visual signals instead of conventional mounted sensors. However, these studies have been focused on measuring displacement response by an image processing technique after recording a position of the target mounted on the structure, in which the number of measurement targets may be limited. Therefore, in this study, a model experiment was carried out to verify the measurement algorithm for measuring multi-point displacement responses by using a DIC (Digital Image Correlation) technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.271-279
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• 2014

In this paper, the two design techniques of the embedded system which provides a wireless image observation with temporary ad-hoc network are proposed and developed. The first method is based on the embedded system design technique for a nearly real-time wireless short observation application, having a specific remote monitoring node with a built-in image processing function, and having the maximum rate of 1 fps (frame per second) wireless image transmission capability of a $160{\times}128$size image. The second technique uses the embedded system for a general wireless long observation application, consisting of the main node, the remote monitoring node, and the system controller with built-in image processing function, and the capability of the wireless image transmission rate of 1/3 fps. The proposed system uses the wireless ad-hoc network which is widely accepted as a short range, low power, and bidirectional digital communication, the hardware are consisted of the general developed modules, a small digital camera, and a PC, and the embedded software based upon the Zigbee stack and the user interface software are developed and tested on the implemented module. The wireless environment analysis and the performance results are presented.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1149-1160
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• 2019

In this study, two radiometric correction methods deriving reflectance from UAV multispectral image for monitoring forest vegetation were applied and evaluated. Multispectral images were obtained from a small multispectral camera having 5 spectral bands. Reflectance were derived by applying the two methods: (1) the direct method using downwelling irradiance measurement and (2) the empirical line correction method by linking a set of field reflectance measured simultaneous with the image capture. Field reflectance were obtained using a spectroradiometer during the flight and used for building the linear equation for the empirical method and for the validation of image reflectance derived. Although both methods provided the high correlations between field reflectance and image-derived reflectance, their distributions were somewhat different. While the direct method provided rather stable and consistent distribution of reflectance all over the entire image area, the empirical method showed very unstable and inconsistent reflectance distribution. The direct method would be more appropriate for relatively wide area that requires more time to acquire image and may vary in downwelling irradiance and atmospheric conditions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.