• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.15-22
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• 2019

In this paper, we proposed a Hangeul detection method using structural features of histogram, consonant, and vowel to solve the problem of Hangul which is separated and detected consonant and vowel The proposed method removes background by using DoG (Difference of Gaussian) to remove unnecessary noise in Hangul detection process. In the image with the background removed, we converted it to a binarized image using a cumulative histogram. Then, the horizontal position histogram was used to find the position of the character string, and character combination was performed using the vertical histogram in the found character image. However, words with a consonant vowel such as '가', '라' and '귀' are combined using a structural characteristic of characters because they are difficult to combine into one character. In this experiment, an image composed of alphabets with various backgrounds, an image composed of Korean characters, and an image mixed with alphabets and Hangul were tested. The detection rate of the proposed method is about 2% lower than that of the K-means and MSER character detection method, but it is about 5% higher than that of the character detection method including Hangul.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.64-73
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• 2012

In this paper, we propose a method to search for identical videos. The proposed method is spatio-temporal group feature fingerprinting. Frame of video is extracted from fixed rate method and is partitioned into vertical group and horizontal group. Descriptor is made of each group feature that is extracted from binary fingerprinting. Next, use descriptor of original video to build a two type of fingerprinting database and matching with query video. To efficient and effective video copy detection, method have high robustness, independence, matching speed. In proposed method, group feature have high robustness and independence in variable modification of video. Building a original fingerprinting database is able to fast matching with query video. The proposed method shows performance improvement in variable modifications in comparison to the existing methods. Especially, very singular performance in speed improvement is great advantage of this paper.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.75-81
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• 2001

In this paper we analyzed the localization error of near-field detection algorithm in the sea. The near-field detection algorithms using triangulation and wavefront curvature basically assume a signal in two dimension of bearing and range. But the assumption causes localization error because there is three dimension of bearing, range, and depth in the sea. Even through three dimensional effect is considered, the localization error is occurred if multipath propagation in the sea is ignored. To analyze the localization error in the sea, we simulate the near-field localization using acoustic propagation model and focused beamforming considering wavefront curvature. The simulation results indicate that localization error always occurs in the sea and the error varied with sound velocity profile, water depth, bottom slope, source range, etc.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.457-466
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• 2010

In this paper, we propose a new method for detecting digital forgery that identify interpolated region between digital composited images. For detecting the interpolation factor and the tampered regions, we perform two algorithms: The first algorithm is to estimate the interpolation factors using the differential equation for forgery image along the horizontal, vertical, and diagonal directions, respectively; The second algorithm is to scan the interpolation factors along each direction for detection areas as the mask of the optical window size($64{\times}64$) in order to find out the forgery region. A detection map of the forgery is classified with the magnitude of estimated interpolation factors into colors. This detection map can be used to find out interpolated regions from the tampered image. Experimental results demonstrate the proposed algorithms are proven on several examples. We also show the proposed approach is to accurately detect interpolated regions from digital composite images.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.193-199
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• 2008

In this paper, it is proposed the implementation of face authentication system based on real-time image processing. We described the process implementing the two steps for real-time face authentication system. At first face detection steps, we describe the face detection by using feature of wavelet transform, LoG operator and hausdorff distance matching. In the second step we describe the new dual-line principal component analysis(PCA) for real-time face recognition. It is combines horizontal line to vertical line so as to accept local changes of PCA. The proposed system is affected a little by the video size and resolution. And then simulation results confirm the effectiveness of out system and demonstrate its superiority to other conventional algorithm. Finally, the possibility of performance evaluation and real-time processing was confirmed through the implementation of face authentication system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.297-303
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• 2007

In this paper, the stroke-based text extraction algorithm for digital video is proposed. The proposed algorithm consists of four stages such as text detection, text localization, text segmentation and geometric verification. The text detection stage ascertains that a given frame in a video sequence contains text. This procedure is accomplished by morphological operations for the pixels with higher possibility of being stroke-based text, which is called as seed points. For the text localization stage, morphological operations for the edges including seed points ate adopted followed by horizontal and vortical projections. Text segmentation stage is to classify projected areas into text and background regions according to their intensity distribution. Finally, in the geometric verification stage, the segmented area are verified by using prior knowledge of video text characteristics.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.1-11
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• 2020

In order to diagnose low-level turbulence in Korea, diagnostic indices of low-level turbulence were calculated from Aug 2016 to Jul 2019 using a Korea Meteorological Administration Post Precessing (KMAPP) developed by the National Institute Meteorological Sciences (NIMS), and the indices were evaluated using Aircaft Meteorological Data Relay (AMDAR). In the mean horizontal distribution of diagnostic indices calculated, severe turbulence was simulated along major domestic mountains, including near the Taebaek Mountains, the Sobaek Mountains and Hallasan Mountain on Jeju Island due to geographical factors. Later, detection performance was evaluated by calculating the KMAPP Low-Level Turbulencd index (KLT) on combined index, using AUC value of Individual diagnostic indices as a weight. The result showed that the AUC value of KLT was 0.73, and the detection performance was improved (0.02-0.13) when the index was combined. Also, when looking for the AMDAR data is divided into years, seasons, and altitudes, up to 0.94 AUC values were found in winter (DJF) and the surface (surface-1,000ft). By using high-resolution numerical data reflecting detailed terrain data, local turbulence distribution was well demonstrated and high detection performance was shown at low-level.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.179-186
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• 2008

Probing inside of concrete structures is one of the important steps in assessing condition of the structure. For the assessment, electromagnetic induction method and electromagnetic wave method are currently applied to the measurement of cover depth, and the detection of reinforcement embedded in concrete. To determine detection capability of locating reinforcement embedded in concrete, commercially available nondestructive testing (NDT) equipments have been tested. The equipments include electromagnetic wave system and electromagnetic induction system. In the tests, nine concrete specimens which have the dimensions of 1,000mm(length))${\times}$300mm(width) with thickness varying from 125mm to 150mm are used. The reinforcement are located at 45, 60, 100mm depth from the concrete surface. Horizontal reinforcement spacing has been set over 100mm. From the outcome, it is shown that error is increased as the diameter of reinforcement enlarge in case of using electromagnetic induction method. In case of using electromagnetic wave method, the detection of reinforcement embedded in deep is good in the view of reliability because of using the relative permittivity on the real cover depth.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1245-1254
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• 2020

In this study, the limitations of the existing water level detection algorithm using CCTV images were recognized and the water level detection algorithm was improved by applying the Region growing technique. It applied three techniques (Horizontal projection profile, Texture analysis, and Optical flow) to estimate the water area, and the results were analyzed in a comprehensive analysis to select the initial water area. The water level was then continuously detected by the Region growing technique, referring to the initial water area. As a result, it was possible to confirm that the exact level of water was detected without being affected by environmental factors compared to the existing level detection algorithm, which had frequent mis-detection phenomena depending on the surrounding environmental factors. In addition, the water level was detected in the video showing flooded roads in urban areas, not in the video of the river. These results are believed to be able to supplement the difficulty of monitoring at all times with limited manpower by automatically detecting the level of water through numerous CCTV footage installed throughout the country, and to contribute to laying the foundation for preventing disasters caused by torrential rains and typhoons in advance.

• Journal of Internet Computing and Services
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• v.25 no.5
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• pp.131-140
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• 2024

Aids to navigation, such as buoys used in maritime environments, play a crucial role in providing accurate information to navigating vessels, enabling them to precisely determine their position and maintain safe routes by marking surrounding hazardous areas. However, collisions between ships and these aids result in substantial costs for buoy damage and repair. While high-end equipment is currently used to prevent such accidents, its widespread adoption is hindered by cost concerns. This paper presents research on a maritime object detection algorithm utilizing embedded systems to address this issue. Previous studies employed the Hough transform for horizon detection, but its high computational demands posed challenges for real-time processing. To overcome this limitation, our approach first performs image segmentation, followed by an optimized Otsu algorithm for horizon detection. Subsequently, we establish a Region of Interest (ROI) based on the detected horizon, focusing on areas with a high risk of ship collision. Within this ROI, particularly below the horizon line, maritime objects are detected. A Convolutional Neural Network (CNN) model is then applied to determine whether the detected objects are ships. Objects classified as ships within the ROI are considered potential collision risks.