• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1305-1316
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• 2018

Graphical user interface(GUI) has a very important role to interact with software users. However, designing and coding of GUI are tedious and pain taking processes. In many studies, the researchers are trying to convert GUI elements or widgets to code or describe formally their structures by help of domain knowledge of stochastic methods. In this paper, we propose the GUI elements detection approach based on object detection strategy using deep neural networks(DNN). Object detection with DNN is the approach that integrates localization and classification techniques. From the experimental result, if we selected the appropriate object detection model, the results can be used for automatic code generation from the sketch or capture images. The successful GUI elements detection can describe the objects as hierarchical structures of elements and transform their information to appropriate code by object description translator that will be studied at future.

• 전기학회논문지
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• 제56권10호
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.54-60
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• 2009

In this paper, a precision landing approach is implemented based on real-time image processing. A full-scale landmark for automatic landing is used. canny edge detection method is applied to identify the outside quadrilateral while circular hough transform is used for the recognition of inside circle. Position information on the ground landmark is uplinked to the unmanned helicopter via ground control computer in real time so that the unmanned helicopter control the air vehicle for accurate landing approach. Ground test and a couple of flight tests for autonomous landing approach show that the image processing and automatic landing operation system have good performance for the landing approach phase at the altitude of $20m{\sim}1m$ above ground level.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1436-1439
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• 1997

The objective of this paper is to present an efficient and practical approach to the automatic classification of power quality(PQ) disturbances, where and orthogonal polynomial approximation method is emloyed for the detection and localization of PQ disturbances, and a feature vector, newly extracted form the bispectra of the detected signal, is utilized for the automatic rectgnition of the various types of PQ disturbances. To demonstrae the performance and applicabiliyt of the proposed approach, some simulation results are provided.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.531-535
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• 1999

Automatic human face detection in a complex background is one of the difficult problems. In this paper, we propose an effective and robust automatic face detection approach that can locate the face region in natural scene images when the system is used as a pre-processor of a face recognition system . We use two natural and powerful visual cues, the skin color and the eyes. In the first step of the proposed system, the method based on the human skin color space by selecting flesh tone regions using normalized r-g space in color images. In the next step, we extract eye features by calculating moments and using geometrical face model. Experimental results demonstrate that the approach can efficiently detect human faces and satisfactory deal with the problems caused by bad lighting condition, skew face orientation.

• 음성과학
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• 제8권2호
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• pp.83-90
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• 2001

We proposed a probabilistic approach of using syllable bigrams to the word-spacing problem. Syllable bigrams are extracted and the frequencies are calculated for the large corpus of 12 million words. Based on the syllable bigrams, we performed three experiments: (1) automatic word-spacing, (2) detection and correction of word-spacing errors for spelling checker, and (3) automatic insertion of a space at the end of line in the character recognition system. Experimental results show that the accuracy ratios are 97.7 percent, 82.1 percent, and 90.5%, respectively.

• 해양환경안전학회지
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• 제14권2호
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• pp.163-168
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• 2008

인공위성 원격탐사를 이용한 선박탐지는 주요 적용 분야 중 하나로, 광역의 환경 감시와 해상보안에 적용되고 있다. 이를 통하여 어장을 포함한 해상교통을 모니터링할 수 있으며, 기름유출 선박을 찾기도 한다. 본 연구에서는, RADARSAT의 합성개구레이더(SAR) 영상을 기반으로 개발한 자동선박탐지기법을 제시하고, 2004년 8월 6일에 얻어진 영상에 적용을 하여 현장 자료와의 비교를 실시하였다. 선박탐지알고리듬은 보정, 랜드마스킹, 필터링, 위치 등록 그리고 식별의 5단계로 구성된다. 울산항을 중심으로 이루어진 위성 촬영시점의 풍속은 최대 0.4m/s이었다. 전장이 68m 이상인 묘박지의 선박을 중심으로 한 선박 탐지 결과는 울산 항만교통정보시스템의 레이더정보와 잘 일치하였다. 바지선과 같은 소형선박의 경우, SAR에 의한 선박 탐지 능력이 육상에 설치된 레이더보다 더 높은 경우도 있었다. 또한, SAR 레이더 산란 단면적(RCS)을 이용하여 선박의 길이와 폭을 계산하였으나, 레이오버와 그림자 효과 때문에 실제 값보다 비교적 높게 추정되었다.

• 한국항행학회논문지
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• 제17권1호
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• pp.115-122
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• 2013

최근 의료영상을 이용한 질병 진단법에 대한 관심이 증가하고 있는 추세이다. 관절경화증은 경동맥의 동맥을 좁게 하여 뇌로 들어가는 혈류의 일부 또는 전체를 차단하는 원인이 된다. 뇌로 흘러가는 혈류가 차단되는 경우 심각한 뇌졸중을 야기하기도 한다. 만일 초기에 경동맥 플라크를 발견하고 이를 치료하면 심각한 뇌졸중을 예방할 수 있다. 본 논문에서는 경동맥의 동맥 초음파 영상에서 경동맥 플라크를 쉽게 발견하기 위한 능동적 윤곽선 추출기법에 기반을 둔 자동 분할기법을 제안한다. 실험에서 사용되는 초음파 영상은 자동 분할기법을 적용하기 전에 적절히 정렬되어있다고 가정한다. 경동맥의 동맥 초음파 영상에 대하여 스네이크 모델을 이용하여 자동분할 방법과 수동분할 방법을 질적 비교한 결과 제안된 방법이 성공적으로 적용되었음을 보여준다. 실험결과 제안된 방법은 방사선사들이 플라크를 쉽게 찾는데 도움을 줄 수 있는 자동화 방법이 될 것으로 예상된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.168-182
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• 2020

Spoofing attacks, especially replay attacks, pose great security challenges to automatic speaker verification (ASV) systems. Current works on replay attacks detection primarily focused on either developing new features or improving classifier performance, ignoring the effects of feature variability, e.g., the channel variability. In this paper, we first establish a mathematical model for replay speech and introduce a method for eliminating the negative interference of the channel. Then a novel feature is proposed to detect the replay attacks. To further boost the detection performance, four post-processing methods using normalization techniques are investigated. We evaluate our proposed method on the ASVspoof 2017 dataset. The experimental results show that our approach outperforms the competing methods in terms of detection accuracy. More interestingly, we find that the proposed normalization strategy could also improve the performance of the existing algorithms.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2219-2226
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• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.