• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.106-114
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• 2018

DEM(Digital Elevation Model) are now easily produced with advancing remote sensing technology. Depending on desired task, UAV can produce high resolution DEM. But high resolution comes with issues of data storage and processing time and cost. To check the effect of DEM resolution, this study compares six geomorphological parameters derived from different resolution DEM in a test area around Chuncheon, Korea. The comparison analysis was based on statistics of each derivatives of slope, curvature, flow direction, flow accumulation, flow length and basin. As a result, it was found that DEM remained unchanged and so did the flow accumulation area. However, slope, curvature, flow length and basin numbers were decreased with the normalization of increasing pixel size. DEM resolution should be carefully selected depending on the precision of application required.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.1-9
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• 2000

In the recent day, the necessity and the effective usage are increased rapidly, and it is applied in many other fields as well as in the field of ortho-photo map. In this study, we extract each objects on the aerial image and automatically classify graphic information to produce digital map using only digital ortho-image without particular drawing devices for producing digital map. For this purpose, we have applied a lot of the image processing techniques and fuzzy theory, classified outline and lane of road and building, and had each layer according to each feature. Especially, in the case of the building, the outer vector lines extracted by pixel unit at the building were very complex, but we have developed the program to be expressed by I-dimensional linear type between building corners. In the result of this study, we could not extract and recognize all of the object on the image all together, but we have got the error within 50cm using semi-automatic technique. Therefore, this method will be used effectively in producing 1/5,000 digital map.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.530-532
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• 2018

Digital imaging equipment has been used for a variety of purposes in a wide range of society and has become an important element of the fourth industrial revolution. However, there are various causes of noise in the process of transmitting / receiving data and processing of the equipment, thus affecting the accuracy and reliability of the equipment. In this paper, we propose an image restoration algorithm based on pixel range set by standard deviation to effectively remove Salt and Pepper noise. In the conventional methods, the performance degrades in the edge and high frequency components of the image. However, the proposed method has better noise reduction performance than the conventional method by performing the noise elimination considering the image boundary. It has confirmed that the performance of such PSNR and magnified image, the experimental results showed that the proposed algorithm superior compared to existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.786-791
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• 2012

This paper presents a depth boundary sharpening method for improved view synthesis in 3D video. In depth coding, distortion occurs around object boundaries, degrading the quality of synthesized images. In order to encounter this problem, the proposed method estimates an edge map for each frame to filter only the boundary regions. In particular, a window-based filter is employed to choose the most reliable pixel as the replacement considering three factors: frequency, similarity and closeness. The proposed method was implemented as post-processing of the deblocking filter in JMVC 8.3.Compared to the conventional methods, the proposed method generated 0.49 dB PSNR increase and 16.58% bitrate decrease on average. The improved portions were subjectively confirmed as well.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.705-711
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• 2011

This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.149-158
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• 2004

This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.90-95
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• 2014

The system design and the system performance analysis of 3D imaging laser radar system for the mapping purpose is addressed in this article. For the mapping, a push-bloom scanning method is utilized. The pulsed fiber laser with high pulse energy and high pulse repetition rate is used for the light source of laser radar system. The high sensitive linear mode InGaAs avalanche photo-diode is used for the laser receiver module. The time-of-flight of laser pulse from the laser to the receiver is calculated by using high speed FPGA based signal processing board. To reduce the walk error of laser pulse regardless of the intensity differences between pulses, the time of flight is measured from peak to peak of laser pulses. To get 3D image with a single pixel detector, Risley scanner which stirs the laser beam in an ellipsoidal pattern is used. The system laser energy budget characteristics is modeled using LADAR equation, from which the system performances such as the pulse detection probability, false alarm and etc. are analyzed and predicted. The test results of the system performances are acquired and compared with the predicted system performance. According to test results, all the system requirements are satisfied. The 3D image which was acquired by using the laser radar system is also presented in this article.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.813-821
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• 2020

Recently, research using unstructured data such as images and videos has been actively conducted in various fields. Edge detection is one of the most useful image enhancement techniques to improve the quality of the image process. However, it is very difficult to perform edge detection in noise images because the edges and noise having high frequency components. This paper uses a linear model and standard deviation as an effective edge detection method for noise images. The edge is detected by the difference between the standard deviation of the pixels included in the pixel block and the standard deviation of the residual obtained by fitting the linear model. The results of edge detection are compared with the results of the Sobel edge detector. In the original image, the Sobel edge detection result and the proposed edge detection result are similar. Proposed method was confirmed that the edge with reduced noise was detected in the various levels of noise images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.103-111
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• 2007

The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.