• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• Geophysics and Geophysical Exploration
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• v.13 no.4
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• pp.315-322
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• 2010

The phase-screen and the split-step Fourier migrations, which are implemented in both the frequency-wavenumber and frequency-space domains by using one-way scalar wave equation, allow imaging in laterally heterogeneous media with less computing time and efficiency. The generalized-screen migration employs the series expansion of the exponential, unlike the phase-screen and the split-step Fourier migrations which assume the vertical propagation in frequency-wavenumber domain. In addition, since the generalized-screen migration generalizes the series expansion of the vertical slowness, it can utilize higher-order terms of that series expansion. As a result, the generalized-screen migration has higher accuracy in computing the propagation with wide angles than the phase-screen and split-step Fourier migrations for media with large and rapid lateral velocity variations. In this study, we developed a 2D prestack generalized-screen migration module for imaging a complex subsurface efficiently, which includes various dips and large lateral variations. We compared the generalized-screen propagator with the phase-screen propagator for a constant perturbation model and the SEG/EAGE salt dome model. The generalized-screen propagator was more accurate than the phase-screen propagator in computing the propagation with wide angles. Furthermore, the more the higher-order terms were added for the generalized-screen propagator, the more the accuracy was increased. Finally, we compared the results of the generalizedscreen migration with those of the phase-screen migration for a model which included various dips and large lateral velocity variations and the synthetic data of the SEG/EAGE salt dome model. In the generalized-screen migration section, reflectors were positioned more accurately than in the phase-screen migration section.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.973-983
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• 2020

Recently, SAR (Synthetic Aperture Radar) is being highlighted as a solution to the coarse spatial resolution of remote sensing data in water resources research field. Spatial resolution up to 10 m of SAR backscattering coefficient has facilitated more elaborate analyses of the spatial distribution of soil moisture, compared to existing satellite-based coarse resolution (>10 km) soil moisture data. It is essential, however, to multilaterally analyze how various hydrological and environmental factors affect the backscattering coefficient, to utilize the data. In this study, soil moisture estimated by WCM (Water Cloud Model) and linear regression is compared with in-situ soil moisture data at 5 soil moisture observatories in the Korean peninsula. WCM shows suitable estimates for observing instant changes in soil moisture. However, it needs to be adjusted in terms of errors. Soil moisture estimated from linear regression shows a stable error range, but it cannot capture instant changes. The result also shows that the effect of soil moisture on backscattering coefficients differs greatly by land cover, distribution of vegetation, and water content of vegetation, hence that there're still limitations to apply preexisting models directly. Therefore, it is crucial to analyze variable effects from different environments and establish suitable soil moisture model, to apply SAR to water resources fields in Korea.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.948-955
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• 2019

As interests in 360-degree VR (Virtual Reality) video services enormously grow, compression and streaming technologies for VR video data have been rapidly developed. Quality Emphasized Region (QER) based streaming scheme has been developed as a kind of viewport-adaptive 360-degree video streaming technology for maintaining immersive experience and reducing bandwidth waste. For selecting a QER corresponding to the user's gaze coordinate, QER-based streaming scheme requires the calculation of Quality Emphasis Center (QEC) distance and signaling message delivery for requesting QER switching. QEC distance calculations require high computational complexity because of repeated calculations as many times as the number of QERs. Furthermore, the signaling message interval results in a trade-off relationship between efficient bandwidth usage and flexible QER switching. In this paper, we propose an improved QER selection algorithm based on MMT protocol to solve this problem. The proposed algorithm could achieve computational complexity reduction by using preprocessed QER_ID_MAP. Also, flexible QER switching could be achieved, as well as efficient bandwidth utilization by an adaptive adjustment of the signaling interval.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.899-909
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• 2021

In Musculoskeletal ultrasound examination, a linear transducer (12-5 MHz) with a contact surface length of 6 cm, which is commonly distributed in medical institutions, does not contact with bent fingers and wrist depressions only by using a conventional liquid ultrasound gel, which causes image loss. In order to solve this image loss, the use of commercially available Water gel pad is increasing. However, it is a disposable medical product. Repeated use is prohibited and expensive. In this study, in order to reduce the economic burden caused by the use of the commercialized Water gel Pad, we searched for water-soluble food thickener powder that can be easily purchased around our lives and manufactured Gel pads. Among them, kappa-Carrageenan Gel Pad, iota-Carrageenan Gel Pad, and Agar-Agar Gel Pad satisfied the evaluation criteria without artifacts in image evaluation using the N-365 Multipurpose Phantom. Also, the price to purchase the food thickener powder was about 38 times cheaper than the existing commercialized Water gel pad. As a result, if you use the food thickener powder such as kappa-Carrageenan, iota-Carrageenan and Agar-Agar to make solidified elastic Gel pad without a cover instead of the commercially available expensive disposable Water gel pad, the convenience and usefulness of use are improved. It is judged that the manufactured Gel pads can contribute well to the role of efficient ultrasound propagation medium.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.465-468
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• 2014

The image processing device sold by the market, which increases the comfort of the driver Around-View of the camera. This system while driving or when parked, came about to prevent accidents caused by driver error or disable the visibility of the system. However, it did not spread widely to the driver due to the problem of the high installation cost and complex installation process from the system for easy operation. Due to problems such as first, expensive equipment and second, the development environment is difficult and third, inconvenient installation process, it is not out because of the prohibitively high cost burden and difficult development environment, programmers and operators. I think if this is solved even one problem of this system would be able to access the user are a little more affordable. In this paper The AVM(Around-View Monitoring) system is proposed, the two problems that minimize expensive equipment, the installation process is inconvenient problem of the three aforementioned systems. Solved the problem caused by a lot of the cost by using low-cost USB device, and a rear camera. Was developed to facilitate the installation is possible by considering the inconvenient installation. Reducing the price paid by consumers because of the system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.49-55
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• 2022

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

• Journal of Platform Technology
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• v.11 no.3
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• pp.24-31
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• 2023

Recently, interest in UAM (Urban Air Mobility, UAM), which can take off and land vertically in the operation of urban air transportation systems, has been increasing. Therefore, various start-up companies are developing related technologies as eco-friendly future transportation with advanced technology. However, studies on ways to increase safety in the operation of UAM are still insignificant. In particular, efforts are more urgent to improve the safety of risks generated in the process of attempting to land in the city center by UAM equipped with autonomous driving. Accordingly, this study proposes a plan to safely land by avoiding dangerous region that interfere when autonomous UAM attempts to land in the city center. To this end, first, the latitude and longitude coordinate values of dangerous objects observed by the sense of the UAM are calculated. Based on this, we proposed to convert the coordinates of the distorted planar image from the 3D image to latitude and longitude and then use the calculated latitude and longitude to compare the pre-learned feature descriptor with the HOG (Histogram of Oriented Gradients, HOG) feature descriptor to extract the dangerous Region. Although the dangerous region could not be completely extracted, generally satisfactory results were obtained. Accordingly, the proposed research method reduces the enormous cost of selecting a take-off and landing site for UAM equipped with autonomous driving technology and contribute to basic measures to reduce risk increase safety when attempting to land in complex environments such as urban areas.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.