• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.53-58
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• 2005

Points of sharp variations in images are the most important components when we analyze singularities of images. And they include a variety of information about the image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now and at the early stage of the research, edge detection operators used relation among neighborhood pixels. However, such methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. For this reason, in this paper we detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in mixed noise environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.35-40
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• 2010

Skyline extraction in mountainous images which has been used for navigation of vehicles or micro unmanned air vehicles is very hard to implement because of the complexity of skyline shapes, occlusions by environments, dfficulties to detect precise edges and noises in an image. In spite of these difficulties, skyline extraction is avery important theme that can be applied to the various fields of unmanned vehicles applications. In this paper, we developed a robust skyline extraction algorithm using two-scale canny edge images, topological information and location of the skyline in an image. Two-scale canny edge images are composed of High Scale Canny edge image that satisfies good localization criterion and Low Scale Canny edge image that satisfies good detection criterion. By applying each image to the proper steps of the algorithm, we could obtain good performance to extract skyline in images under complex environments. The performance of the proposed algorithm is proved by experimental results using various images and compared with an existing method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1132-1140
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• 1997

In many vision tasks of the major obstacles is the specular highkight of smoth objects, which causes a misinterpretation of objects.This paper presents an dffcient algorithm for highight detection and object reconstruction, blsed on the theory of photometric stereo in which the location of highilight changes as the position of illumination source changes.Two images, referred to as base image and reference image.are sequentially taken with two different positionhs of the two images.The difference image is thresholded to detct the specular spike of the highlight.Then the specu-lar lobe around the specular spike is detected to reconstruct the object.The proposed algorithm can be applied to metals and dielectrics, regardlless of the surface chracteristics.This method can also be aplied to the case when the background is brighter than the object.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5471-5478
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• 2012

In this paper, we propose a new short-circuit detecting method which can detect bad short-circuits, one of bad types occurring in PCB(Printed Circuit Board), by using SURF(Speeded-Up Robust Features) algorithm. The basic procedure in the proposed method sequentially consists of extracting features from both sample and inputted images by SURF, performing perspective transform by feature matching and matching results, extracting check areas of interest, binary coding and extracting short-circuits, and verifying results. The proposed method focuses on the robustness which can detect bad short-circuits even though the position and angle of PCB are not uniform and arbitrarily placed. Experimental results show that our method enables to detect bad short-circuits regardless of the location and angle of PCB placed variously and validate that the proposed method outperforms the conventional methods detecting bad short-circuits manually on the aspect of both the detection rate and time.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.1-8
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• 2020

If a dangerous situation arises in a place where out of reach from the human, UAVs can be used to determine the size and location of the situation to reduce the further damage. With this in mind, this paper sets the minimum value of the roll, pitch, and yaw using beta flight to detect the UAV's smooth hovering, integration, and derivative (PID) values to ensure that the UAV stays horizontal, minimizing errors for safe hovering, and the camera uses Open CV to install the Raspberry Pi program and then HSV (color, saturation, Brightness) using the color palette, the filter is black and white except for the red color, which is the closest to the fire we want, so that the UAV detects the image in the air in real time. Finally, it was confirmed that hovering was possible at a height of 0.5 to 5m, and red color recognition was possible at a distance of 5cm and at a distance of 5m.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.345-352
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• 2017

We propose a methods which is reducing direction estimation error of sound source in the reverberant and noisy environments. The proposed algorithm divides speech signal into voice and unvoice using VAD. We estimate the direction of source when current frame is voiced. TDOA (Time-Difference of Arrival) between microphone array using the GCC-PHAT (Generalized Cross Correlation with Phase Transform) method will be estimated in that frame. Then, we compare the peak value of cross-correlation of two signals applied to estimated time-delay with other time-delay in time-table in order to improve the accuracy of source location. If the angle of current frame is far different from before and after frame in successive voiced frame, the angle of current frame is replaced with mean value of the estimated angle in before and after frames.

• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.7-16
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• 2015

A segmentation process extracts an interesting area of barcode in an image and gives a crucial impart on the performance of barcode verifier. Previous segmentation methods occurs some issues as follows. First, it is very hard to determine a threshold of length in Hough Line transform because it is sensitive. Second, Morphology transform delays the process when you conduct dilation and erosion operations during the image extraction. Therefore, we proposes a novel Converged Harris Corner detection-based segmentation method to detect an interesting area of barcode in Data Matrix. In order to evaluate the performance of proposed method, we conduct experiments by a dataset of barcode in accordance with size and location in an image. In result, our method solves the problems of delay and surrounding environments, threshold setting, and extracts the barcode area 100% from test images.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.70-79
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• 2017

This study proposes a method to quickly and accurately acquire distance information on direction signs. The proposed method is composed of the recognition of the sign, pre-processing to facilitate the acquisition of the road sign distance, and the acquisition of the distance data. The road sign recognition uses color detection including gamma correction in order to mitigate various noise issues. In order to facilitate the acquisition of distance data, this study applied tilt correction using linear factors, and resolution correction using Fourier transform. To acquire the distance data, morphological operation was used to highlight the area, along with labeling and template matching. By acquiring the distance information on the direction sign through such a processes, the proposed system can be output the distance remaining to the next junction. As a result, when the proposed method is applied to system it can process the data in real-time using the fast calculation speed, average speed was shown to be 0.46 second per frame, with accuracy of 0.65 in similarity value.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.5
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• pp.494-498
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• 2004

Fire accidents often happen in large buildings because large buildings are equipped with heavy electrical wiring and piping. When fire is to be occurred in those buildings, it is very dangerous to People and building structures. Therefore, multi-point wireless temperature sensors for large buildings are necessary in order to detect fire in the early time and thus to minimize the loss. A wireless device was composed of the transmitter and receiver. The specification of this device was as follows: 915MHz of transmitted frequency, 4 channels, 9600bps of the transmitted speed, and 10mW of the transmitted power. We confirmed through experiment that the temperature was well sensed and fire location was determined by the 4 channel sensors of the developed sensor system.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.345-354
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• 2005

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have a priori knowledge about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper presents the motion detection algorithm that can run robustly about recusive motion. The motion detection compares and analyzes two frames each other, motion of whether happened judge. Through experiments, we show significant improvements in the reduction of the computational time in terms of the number of search steps without much quality degradation in the predicted image.