• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.479-482
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• 2003

Edge, detected from image processing includes variety of information about original image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now. And with the recent progress of wavelet theory which is presented as a new technique of signal processing fields, wavelet transform is being applied to many fields which analyzes singularities of image. For this reason, this paper detected original image's edge from the information such as local maximum, direction, and location of the wavelet transform data by using wavelet function which is independent of width of line.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.792-798
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• 2004

In this paper, we will introduce a new corner detector for the wafer die position recognition. The die position recognition procedure is necessary for WSCSP(Wafer Scale Chip Scale Packaging) technology, decide the accuracy of post-procedure. We present a hierarchical gray level corner detection method for the recognition of the die position from a wafer image. The new corner detector divides the corner region into many homocentric circles, and calculates the comer response and the angle of direction about each circle to get an accurate toner point. The new corner detector has a hierarchical structure so it can detect comer point more quickly than general gray level corner detector.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.139-147
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• 2014

In this paper, we present a novel method for simultaneous detection and tracking of multiple objects using dual-layer particle filtering. The proposed dual-layer particle sampling (DLPS) algorithm consists of parent-particles (PP) in the first layer for detecting multiple objects and child-particles (CP) in the second layer for tracking objects. In the first layer, PPs detect persons using a classifier trained by the intersection kernel support vector machine (IKSVM) at each particle under a randomly selected scale. If a certain PP detects a person, it generates CPs, and makes an object model in the detected object region for tracking the detected object. While PPs that have detected objects generate CPs for tracking, the rest of PPs still move for detecting objects. Experimental results show that the proposed method can automatically detect and track multiple objects, and efficiently reduce the processing time using the sampled particles based on motion distribution in video sequences.

• Journal of Radiation Protection and Research
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• v.25 no.1
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• pp.3-9
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• 2000

The Korea Atomic Energy Research Institute acquired the Lawrence Livermore National Laboratory phantom for calibration of germanium detectors used for in vivo measurement of radionuclides deposited in human lungs. The manufacturer inscribed concentric circles as a phoswich detector positioning guides on the phantom's torso plate and its overlay plates, and provided the effective thickness of the chest wall for each plate measured at locations over the circles. However, since the germanium detectors are of different sizes, the areas considered for phoswich detectors were no. longer applicable for the locations of the germanium detectors on the phantom. Therefore, we re-evaluated the effective thickness of the phantom to determine if the manufacturer' s data are valid for germanium detectors in use for in vivo lung counting or if new values must be implemented. Differences no more than 3% in effective thickness were found between the germanium detector regions to be used at the Korea Atomic Energy Research Institute and the phoswich detector regions prescribed by the manufacturer.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.607-611
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• 2008

This paper proposes new video signature using spatio-temporal information for copy detection. The proposed video copy detection method is based on concentric circle partitioning method for each key frame. Firstly, key frames are extracted from whole video using temporal bilinear interpolation periodically and each frame is partitioned as a shape of concentric circle. For the partitioned sub-regions, 4 feature distributions of average intensity, its difference, symmetric difference and circular difference distributions are obtained by using the relation between the sub-regions. Finally these feature distributions are converted into binary signature by using simple hash function and merged together. For the proposed video signature, the similarity distance is calculated by simple Hamming distance so that its matching speed is very fast. From experiment results, the proposed method shows high detection success ratio of average 97.4% for various modifications. Therefore it is expected that the proposed method can be utilized for video copy detection widely.

• Journal of Food Hygiene and Safety
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• v.39 no.2
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• pp.152-162
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• 2024

In this study, we investigated the levels of the natural preservatives, benzoic acid, sorbic acid, and propionic acid, in raw unprocessed vegetables. Quantitative analysis of benzoic acid and sorbic acid was performed using high-performance liquid chromatography with a diode array detector (HPLC-DAD) and confirmed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Propionic acid was analyzed using a gas chromatography-flame ionization detector (GC-FID) and confirmed using gas chromatography-mass spectrometry (GC-MS). From a total of 497 samples, benzoic acid, sorbic acid, and propionic acid were found in 50 (10%), 8 (0.2%), and 61 samples (12.3%), respectively. The highest quantity of benzoic acid, sorbic acid, and propionic acid was found in peony root (1,057 mg/kg), nut-bearing torreya seeds (27.3 mg/kg), and myrrha (175 mg/kg), respectively. The background concentration range of naturally occurring preservatives in raw vegetables determined in this study could be used as standard inspection criteria to address consumer complaints and trade disputes.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.1-12
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• 2019

A dialog system becomes a new way of communication between human and computer. The dialog system takes human voice as an input, and gives a proper response in voice or perform an action. Although there are several well-known products of dialog system (e.g., Amazon Echo, Naver Wave), they commonly suffer from a problem of out-of-domain utterances. If it poorly detects out-of-domain utterances, then it will significantly harm the user satisfactory. There have been some studies aimed at solving this problem, but it is still necessary to study about this intensively. In this paper, we give an overview of the previous studies of out-of-domain detection in terms of three point of view: dataset, feature, and method. As there were relatively smaller studies of this topic due to the lack of datasets, we believe that the most important next research step is to construct and share a large dataset for dialog system, and thereafter try state-of-the-art techniques upon the dataset.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.49-54
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• 1999

In this paper, we propose a new method to estimate the initial DOA of a new appearing source in wideband multisource beamforming and tacking with array sensor position calibration algorithm. By using a beampattern formula for initial DOA detection, the proposed method keeps estimation error within possible tracking range and can be applied to several beamformers with different mainlobe width by adjusting DOA resolution. The simulation results show the performances of source detection and tracking.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.280-281
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• 2003

광도 측정의 기본단위인 칸델라 눈금을 확립하는 방법에는 흑체에서 방출되는 분광복사휘도를 기준으로 사용하는 광원 기반 방법과 극저온 절대 복사계(absolute cryogenic radiometer； ACR)로 부터 출발하여 실현하는 검출기 기반의 두 가지 방법이 사용된다. ACR를 사용하면서 검출기 기반 칸델라 눈금의 불확도가 흑체의 온도 측정 불확도로부터 전파되는 불확도 보다 휠씬 작기 때문에 각국의 국가 측정 표준 대표기관에서 검출기 기반 칸텔라 눈금을 실현하고, 교정이나 측정 서비스를 제공하고 있다. (중략)

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.427-428
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• 2007

컴퓨터 비전을 이용한 이진 영상 데이터 처리는 사용자가 원하는 객체를 배경과 분리하여 추출하는 데에 유용하며 객체 위치 검출에는 테두리 검출(edge detection), 센트로이드 검출 (centroid detection) 등 다양한 기법들이 사용되어 왔다. 연속해서 움직이는 객체의 위치를 테두리 검출 기법을 이용하여 추종 시, 조명과 환경 잡음에 민감한 영상 데이터의 특성상 객체의 테두리 부분은 매 프레임마다 조금씩 차이가 있어 위치를 검출하는 데에 오차가 발생하기 쉽다. 그러나 센트로이드 기법으로 구할 경우 많은 픽셀의 무게중심을 구하는 것이므로 그 오차를 줄여 빠르고 정확한 위치 검출에 유용하다. 본 논문에서는 LabVIEW를 이용하여 진자운동 하는 물체의 센트로이드 점을 구하여 실시간 위치 검출을 구현한다.