• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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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.

• 디지털산업정보학회논문지
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• 제11권4호
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• pp.89-97
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• 2015

In this paper, a method of color image segmentation based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) using compactness of superpixels and texture information is presented. The DBSCAN algorithm can generate clusters in large data sets by looking at the local density of data samples, using only two input parameters which called minimum number of data and distance of neighborhood data. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. Each superpixel is consist of pixels with similar features such as luminance, color, textures etc. Superpixels are more efficient than pixels in case of large scale image processing. In this paper, superpixels are generated by SLIC(simple linear iterative clustering) as known popular. Superpixel characteristics are described by compactness, uniformity, boundary precision and recall. The compactness is important features to depict superpixel characteristics. Each superpixel is represented by Lab color spaces, compactness and texture information. DBSCAN clustering method applied to these feature spaces to segment a color image. To evaluate the performance of the proposed method, computer simulation is carried out to several outdoor images. The experimental results show that the proposed algorithm can provide good segmentation results on various images.

• 한국정보통신학회논문지
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• 제18권7호
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• pp.1734-1739
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• 2014

현재, 디지털 시대의 급속 발전과 함께 멀티미디어 관련 영상 장치들이 대중화 되고 있다. 그러나 영상 데이터를 처리하는 과정에서 임펄스 잡음에 의해 영상이 훼손되어 영상 인식이 어렵게 되며, 이러한 영상을 복원하기 위해 활발한 연구가 진행되고 있다. 본 논문에서는 임펄스 잡음환경에서 훼손된 영상을 복원하기 위해 훼손된 화소를 중심으로 방향성과 화소 사이의 공간적 거리에 따라 가중치를 적용하는 영상복원 필터 알고리즘을 제안하였다. 그리고 개선 효과의 객관적 판단 기준으로 PSNR(peak signal to noise ratio)을 사용하여 기존의 방법들과 비교하였다.

• 스마트미디어저널
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• 제5권3호
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• pp.93-98
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• 2016

배회란 "어떤 곳을 중심으로 어슬렁거리며 이리저리 돌아다닌다." 라는 사전적인 의미를 가지고 있으며 대부분의 범죄가 발생하기 전에 이루어지는 행동이다. 따라서 배회행위를 검출함으로써 다양한 범죄를 사전에 예방할 수 있다. 본 논문에서는 Raspberry Pi를 이용한 배회행위 검출 알고리즘을 제안한다. 제안한 알고리즘은 적응형 차영상을 이용해 움직이는 객체를 검출하였고, 객체검출의 정확성을 높이기 위해 모폴로지 열림 연산을 사용한다. 객체가 검출되면 객체의 무게중심점을 이용하여 무게중심점의 각도 변화와 객체의 높이에 반비례하는 픽셀 이동 거리를 이용하여 배회행위를 검출한다. 배회행위로 검출되면 Raspberry Pi를 이용하여 경고음을 출력하여 사용자에게 알려준다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.885-888
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• 2018

This paper researches a way of detecting fish robots moving in an aquarium. The fish robot was designed and developed for interactions with humans in aquariums. It was studied merely to detect a moving object in an aquarium because we need to find the positions of moving fish robots. The intention is to recognize the location of robotic fish using an image processing technique and a video camera. This method is used to obtain the velocity for each pixel in an image, and assumes a constant velocity in each video frame to obtain positions of fish robots by comparing sequential video frames. By using this positional data, we compute the distance between fish robots using a mathematical expression, and determine which fish robot is leading and which one is lagging. Then, the lead robot will wait for the lagging robot until it reaches the lead robot. The process runs continuously. This system is exhibited in the Busan Science Museum, satisfying a performance test of this algorithm.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.187-187
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• 2016

High intensity of population distribution in deltaic setting especially in Asia tends to have increased and causes coastal flood risk due to lower elevations and significant subsidence. Maximum or peak discharge of flood always causes numerous deaths and huge economic losses. New technology of spatial satellite image has been applied to analyze flood damage. In this research, the relationship of nightlight intensity associated with flood damages has been determined during 1992-2013 with spatial resolution of 30 arc sec ($0.0083^{\circ}$) which is nearly one kilometer at the equator in whole six countries along the Mekong River (i.e., China, Myanmar, Lao PDR, Thailand, Cambodia and Vietnam). ArcGIS Hydrological Flow Length Tool has been used to determine the distance of each pixel areas from the rivers and streams. Statistical analysis results highlight the significant correlation R = 0.47 between nightlight digital number and economic damages per unit area (US$/km2) and R = 0.62 for number of affected people for unit area ($people/km^2$). The areas near by the Mekong River and its tributaries correspond to high flood damage. This spatial analysis result is going to be prestigious key information to the regions and all related stakeholders for decisions and mitigation strategies.

• Journal of the Optical Society of Korea
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• 제17권1호
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• pp.50-56
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• 2013

Optical-fiber electronic speckle pattern interferometry (ESPI) is a non-contact, non-destructive examination technique with the advantages of rapid measurement, high accuracy, and full-field measurement. The optical-fiber ESPI system used in this study was compact and portable with the advantages of easy set-up and signal acquisition. By suitably configuring the optical-fiber ESPI system, producing an image signal in a charge-coupled device camera, and periodically modulating beam phases, we obtained phase information from the speckle pattern using a four-step phase shifting algorithm. Moreover, we compared the actual defect size with that of interference fringes which appeared on a screen after calculating the pixel value according to the distance between the object and the CCD camera. Conventional methods of measuring defects are time-consuming and resource-intensive because the estimated values are relative. However, our simple method could quantitatively estimate the defect length by carrying out numerical analysis for obtaining values on the X-axis in a line profile. The results showed reliable values for average error rates and a decrease in the error rate with increasing defect length or pressure.

• 한국공간구조학회논문집
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• 제21권3호
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• pp.25-34
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• 2021

This study develops a new device system for measuring a slope of object with non-adhesive, non-contact and non-face-to-face, namely Inclinometer Slope Laser Measuring (ISLM), that is applicable in the field. This system includes cradle, laser, camera, and computer and the filming and is performed after laser projection at programmed intervals. After measuring the amount of displacement converted to numerical values, these values can then be transferred to the office using the selected data transmission method. The obtained results from the test carried out to verify the reliability of the ISLM system indicated that the ISLM system can measure with accurately level of 0.1mm/Pixel at 1m distance and when increasing the camera resolution, the precision might increase proportionally. Therefore, the proposed measure system may widely apply on-site for various constructions, especially, in the case of object with very high surface temperature where exhibits difficulty to directly measure the adjacent structures. However, due to the sensitive reaction to the illuminance, this method can be applied with caution at times of large changes in illuminance, such as at dawn and at dusk.

• Nuclear Engineering and Technology
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• 제54권2호
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• pp.601-607
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• 2022

In recent years, monitoring of spent nuclear fuel inside dry cask storage has become an important area of national security. Muon tomography is a useful method for monitoring spent nuclear fuel because it uses high energy muons that penetrate deep into the target material and provides a 3-D structure of the inner materials. We designed a muon tomography system consisting of four 2-D position sensitive detector and characterized and optimized the system parameters. Each detector, measuring 200 × 200 cm², consists of a plastic scintillator, wavelength shifting (WLS) fibers and, SiPMs. The reconstructed image is obtained by extracting the intersection of the incoming and outgoing muon tracks using a Point-of-Closest-Approach (PoCA) algorithm. The Geant4 simulation was used to evaluate the performance of the muon tomography system and to optimize the design parameters including the pixel size of the muon detector, the field of view (FOV), and the distance between detectors. Based on the optimized design parameters, the spent fuel assemblies were modeled and the line profile was analyzed to conduct a feasibility study. Line profile analysis confirmed that muon tomography system can monitor nuclear spent fuel in dry storage container.

• 자동차안전학회지
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• 제13권4호
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.