• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.143-149
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• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.284-293
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• 2015

The objective of this paper is to determine the conditions of road surface by utilizing the images collected from closed-circuit television (CCTV) cameras installed on roadside. First, a technique was examined to detect wet surfaces at nighttime. From the literature reviews, it was revealed that image processing using polarization is one of the preferred options. However, it is hard to use the polarization characteristics of road surface images at nighttime because of irregular or no light situations. In this study, we proposes a new discriminant for detecting wet and dry road surfaces using CCTV image data at night. To detect the road surface conditions with night vision, we applied the wavelet packet transform for analyzing road surface textures. Additionally, to apply the luminance feature of night CCTV images, we set the intensity histogram based on HSI(Hue Saturation Intensity) color model. With a set of 200 images taken from the field, we constructed a detection criteria hyperplane with SVM (Support Vector Machine). We conducted field tests to verify the detection ability of the wet road surfaces and obtained reliable results. The outcome of this study is also expected to be used for monitoring road surfaces to improve safety.

• 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.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of the Korean Society of Radiology
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• v.13 no.7
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• pp.955-960
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• 2019

The Computed tomography (CT) scan can have high radiation in a few tests, and this risk is significant given that it is often repeated in one patient. In children, the incidence of radiation-induced cancer is reported because organs are growing, are more sensitive to radiation. 3D printing has recently been studied to be applied to various applications as a research field for 3D printing applications, research on fabrication of radiation shields and materials has been conducted. The purpose of the 3D printer is to replace the existing panel-type shields and to make customized designs according to the shape of the human body. Therefore, research on 3D information processing to be input to the 3D printer is also necessary. In this study, 3D data of the human body surface, which is the preliminary step of the manufacture of patient-specific eye shield using stereo vision depth map technology, was studied. This study aims to increase the possibility of three-dimensional output. As a result of experimenting with this method, which is relatively simple compared with other methods of 3D information processing, the minimum coordinates for 3D information are extracted. The results of this study provided the advantages and limitations of stereo images using natural light and will be the basic data for the manufacture of eye shields in the future.

• Archives of design research
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• v.14 no.4
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• pp.117-126
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• 2001

A new functional meaning has been given as natural resource to bamboo through reanalysis. Bamboo products contributed to creating added-value of pro-environment. In this study, a potential efficiency and vision of bamboo products and crafts are presented. As bamboo plywood and bamboo decorating paper were developed followed by academic and technological support, an activation of markets has been pursued and bamboo pattern tiles for new furniture was developed. This study examined kinds and characteristics of bamboo and processing of raw material and how to express with the material. Through advanced technology, it identified traditional functions and technological mistakes and analysed domestic and overseas applications to enhance utility of plywood made of bamboo. Bamboo pattern tiles were developed for decorating of furniture doors based on bamboo pattern paper. For patterns, 'tortoise, cranes, and deer'meaning eternity and new millenium among Ten Korean Longevity Animals are simply and lively represented. Series of the sun and mountain use effects of bamboo pieces to present bright images and to maximize quality of bamboo. A pattern of '卍'incorporates mystery of the cosmos and meaning of temples together with traditional patched wrapping cloth, Arirang and Chilgyopannori for beautiful ornamentation. Bamboo decorating tiles are made through accumulation of technologies by a cooperation with industries of bamboo equipment and production of furniture in Damyang Bamboo Products Complex. Processing of raw materials is peformed with equipment of Damyang. Development of samples and production and delivery of bamboo goods are handled in Design Venture of Chosun University Chamber. Developed goods decorating doors of furniture are in sale by an order from furniture industries.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.689-699
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• 2016

As the demand for LCD increases, the importance of inspection equipment for improving the efficiency of LCD production is continuously emphasized. The pattern inspection apparatus is one that detects minute defects of pattern quickly using optical equipment such as line scan camera. This pattern inspection apparatus makes a decision on whether a pixel is a defect or not using a single threshold value in order to meet constraint of real time inspection. However, a method that uses an adaptive thresholding scheme with different threshold values according to characteristics of each region in a pattern can greatly improve the performance of defect detection. To apply this adaptive thresholding scheme it has to be known that a certain pixel to be inspected belongs to which region. Therefore, this paper proposes a region matching algorithm that recognizes the region of each pixel to be inspected. The proposed algorithm is based on the pattern matching scheme with the consideration of real time constraint of machine vision and implemented through GPGPU in order to be applied to a practical system. Simulation results show that the proposed method not only satisfies the requirement for processing time of practical system but also improves the performance of defect detection.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.157-168
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• 2016

In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.1-8
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• 2008

The belief propagation method that has been studied recently yields good performance in disparity extraction. The method in which a target function is modeled as an energy function based on Markov random field(MRF), solves the stereo matching problem by finding the disparity to minimize the energy function. MRF models provide robust and unified framework for vision problem such as stereo and image restoration. the belief propagation method produces quite correct results, but it has difficulty in real time implementation because of higher computational complexity than other stereo methods. To relieve this problem, in this paper, we propose a fast algorithm of the belief propagation method. Energy function consists of a data term and a smoothness tern. The data term usually corresponds to the difference in brightness between correspondences, and smoothness term indicates the continuity of adjacent pixels. Smoothness information is created from messages, which are assigned using four different message arrays for the pixel positions adjacent in four directions. The processing time for four message arrays dominates 80 percent of the whole program execution time. In the proposed method, we propose an algorithm that dramatically reduces the processing time require in message calculation, since the message.; are not produced in four arrays but in a single array. Tn the last step of disparity extraction process, the messages are called in the single integrated array and this algorithm requires 1/4 computational complexity of the conventional method. Our method is evaluated by comparing the disparity error rates of our method and the conventional method. Experimental results show that the proposed method remarkably reduces the execution time while it rarely increases disparity error.