• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.53-62
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• 2013

This paper proposes a method of automatically predicting the vanishing point for the purpose of detecting the road region from natural images. The proposed method stably detects the vanishing point in the road environment by analyzing the dominant orientation of the image and predicting the vanishing point to be at the position where the feature components of the image are concentrated. For this purpose, in the first stage, the image is partitioned into sub-blocks, an edge sample is selected randomly from within the sub-block, and RANSAC is applied for line fitting in order to analyze the dominant orientation of each sub-block. Once the dominant orientation has been detected for all blocks, we proceed to the second stage and randomly select line samples and apply RANSAC to perform the fitting of the intersection point, then measure the cost of the intersection model arising from each line and we predict the vanishing point to be located at the average point, based on the intersection point model with the highest cost. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for detecting the vanishing point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2312-2325
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• 2013

In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2412-2420
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• 1997

An algorithm for detecting dominant points on a digital contour is proposed. The algorithm detects the dominant points from the given contour with the given number of points as a constraint condition. on the basis of the principle of the top-down approach. The dominant points are detected by minimizing the object function that presents the similarity between the given contour and the approximated polygon drawn by connecting the dominant points of candicate. The penalty multiplier method is applied to minimize the augmented Lagrangean function which is made by adding the penalty of the constraint condition to the object function. On the minimization, a local searching method by the partial problem division is considered, and it is clarified that the reasonable solution is obtained by the method. The proposed algorithm has a merit that the dominant points can be detected exactly and stably even for the digital contour composed of multiple-scale features and the similar contours, because it detects them on considering the property of a whole figure of the given contour. It is confirmed that the proposed algorithm is more excellent than other previously proposed algorithms by the comparison and the evaluation through the experiment on suing typical digital curves.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.277-285
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• 2010

This paper describes an approach to analyze geometrical information of building images for understanding outdoor environment of autonomous navigation robot. Line segments and color information are used to classily a building with the other objects such as sky, trees, and roads. The line segments and their two neighboring regions are extracted from detected edges in image. The model of line segment (MLS) consists of color information of neighbor regions. This model rules out the line segments of non-building face. A building face converges into dominant vanishing points (DVPs) which include one vertical point and one of five horizontal points in maximum. The intersection of vertical and horizontal lines creates a facet of building. The geometrical characteristics such as the center coordinates, area, aspect ratio and aligned coexistence are used for extracting the windows in the building facet. In experiments, 150 building faces and 1607 windows were detected from the database of outdoor environment. We found that this result shows 94.46% detection rate. These experimental images were all taken in Ulsan metropolitan city in Korea under difference of viewpoints, daytime, camera system and weather condition.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.48-55
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• 2008

In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.

• Clinical and Experimental Pediatrics
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• v.62 no.5
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• pp.193-197
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• 2019

Alport syndrome (ATS) is an inherited glomerular disease caused by mutations in one of the type IV collagen novel chains (${\alpha}3$, ${\alpha}4$, and ${\alpha}5$). ATS is characterized by persistent microscopic hematuria that starts during infancy, eventually leading to either progressive nephritis or end-stage renal disease. There are 3 known genetic forms of ATS, namely X-linked ATS, autosomal recessive ATS, and autosomal dominant ATS. About 80% of patients with ATS have X-linked ATS, which is caused by mutations in the type IV collagen ${\alpha}5$ chain gene, COL4A5. Although an 80% mutation detection rate is observed in men with X-linked ATS, some difficulties do exist in the genetic diagnosis of ATS. Most mutations are point mutations without hotspots in the COL4A3, COL4A4, and COL4A5 genes. Further, there are insufficient data on the detection of COL4A3 and COL4A4 mutations for their comparison between patients with autosomal recessive or dominant ATS. Therefore, diagnosis of ATS in female patients with no apparent family history can be challenging. Therefore, in this study, we used whole-exome sequencing (WES) to identify mutations in type IV collagen in 2 girls with glomerular basement membrane structural changes suspected to be associated with ATS; these patients had no relevant family history. Our results revealed de novo c.4688G>A (p.Arg1563Gln) and c.2714G>A (p.Gly905Asp) mutations in COL4A5. Therefore, we suggest that WES is an effective approach to obtain genetic information in ATS, particularly in female patients without a relevant family history, to detect unexpected DNA variations.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.355-364
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• 2022

In this study a tendency of abnormal sea surface temperature (SST) occurrence in the seas around South Korea is analyzed from daily SST data from satellite and 14 buoys from August 2020 to July 2021. As thresholds 28℃ and 4℃ are used to determine marine heatwaves(MHWs) and abnormal low water temperature (ALWT), respectively, because those values are adopted by the National Institute of Fisheries Science for the breaking news of abnormal temperature. In order to calculate frequency of abnormal SST occurrence spatially by using satellite SST, research area was divided into six areas of coast and three open seas. ALWT dominantly appeared over a wide area (7,745 km²) in Gyeonggi Bay for total 94 days and it was also confirmed from buoy temperature showing an occurrence number of 47 days. MHWs tended to be high in frequency in the coastal areas of Chungcheongdo and Jeollabukdo and the south coastal areas while in case of buoy temperature Jupo was the place of high frequency (32 days). This difference was supposed to be due to the low accuracy of satellite SST at the coasts. MHWs are also dominant in offshore waters around Korean Peninsula. Although detecting abnormal SST by using satellite SST has advantage of understanding occurrence from a spatial point of view, we also need to perform detection using buoys to increase detection accuracy along the coast.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.589-599
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• 2024

This study presents the usability of the high-rate single-frequency Precise Point Positioning (SF-PPP) technique based on 20 Hz Global Positioning Systems (GPS)-only observations in detecting dynamic motions. SF-PPP solutions were obtained from post-mission and real-time GNSS corrections. These include the International GNSS Service (IGS)-Final, IGS real-time (RT), real-time MADOCA (Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis), and real-time products from the Australian/New Zealand satellite-based augmentation systems (SBAS, known as SouthPAN). SF-PPP results were compared with LVDT (Linear Variable Differential Transformer) sensor and single-frequency relative positioning (SF-RP) solutions. The findings show that the SF-PPP technique successfully detects the harmonic motions, and the real-time products-based PPP solutions were as accurate as the final post-mission products. In the frequency domain, all GNSS-based methods evaluated in this contribution correctly detect the dominant frequency of short-term harmonic oscillations, while the differences in the amplitude values corresponding to the peak frequency do not exceed 1.1 mm. However, evaluations in the time domain show that SF-PPP needs high-pass filtering to detect accurate displacement since SF-PPP solutions include trends and low-frequency fluctuations, mainly due to atmospheric effects. Findings obtained in the time domain indicate that final, real-time, and MADOCA-based PPP results capture short-term dynamic behaviors with an accuracy ranging from 3.4 mm to 8.5 mm, and SBAS-based PPP solutions have several times higher RMSE values compared to other methods. However, after high-pass filtering, the accuracies obtained from PPP methods decreased to a few mm. The outcomes demonstrate the potential of the high-rate SF-PPP method to reliably monitor structural and earthquake-induced ground motions and vibration frequencies of structures.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.511-520
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• 2009

In this study, the Ocean Tide Loading (OTL) constituents were detected by the Precise Point Positioning (PPP) technique using GPS. Then, the GPS estimates of OTL constituents were compared with the predictions of the ocean tide models. We picked three permanent GPS stations as test sites and they are ICNW, SEOS, and CJUN. To detect the OTL constituents using GPS, we created vertical coordinate time series at 10-minute intervals using the PPP approach implemented in the GIPSY software. Through the tidal harmonic analysis of this height time series, the four major constituents ($M_2$, $S_2$, $K_1$, $O_1$) were determined. The amplitude obtained from the GPS height time series of the OTL constituents showed best match with the model predictions at CJUN, while the phase showed closest match at ICNW. The amplitude accuracy of the $M_2$, which is the dominant factor out of the 11 major constituents, was 24.8% on average.

• Journal of The Korean Astronomical Society
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• v.51 no.5
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• pp.129-142
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• 2018

The DEEP-South (the Deep Ecliptic Patrol of the Southern Sky) photometric census of small Solar System bodies produces massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of multi-aperture photometry and FastBit indexing techniques for faster access to a portion of the DEEP-South year-one data. Our new pipeline is designed to perform automated point source detection, robust high-precision photometry and calibration of non-crowded fields which have overlap with previously surveyed areas. In this paper, we show some examples of catalog-based variability searches to find new variable stars and to recover targeted asteroids. We discover 21 new periodic variables with period ranging between 0.1 and 31 days, including four eclipsing binary systems (detached, over-contact, and ellipsoidal variables), one white dwarf/M dwarf pair candidate, and rotating variable stars. We also recover astrometry (< ${\pm}1-2$ arcsec level accuracy) and photometry of two targeted near-earth asteroids, 2006 DZ169 and 1996 SK, along with the small- (~0.12 mag) and relatively large-amplitude (~0.5 mag) variations of their dominant rotational signals in R-band.