• 한국정보통신학회논문지
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• 제24권3호
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• pp.378-383
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• 2020

Viola & Jones의 객체 검출 알고리즘은 얼굴 요소 검출을 위한 매우 우수한 알고리즘이지만 변수 설정에 따른 중복 검출, 오 검출, 미 검출 같은 문제들이 여전히 존재한다. 본 논문은 Viola & Jones의 객체 검출 알고리즘에 미 검출을 줄이기 위한 가변 변수와 중복 검출과 오 검출을 줄이기 위한 검증을 적용한 개선된 얼굴 요소 검출 알고리즘을 제안한다. 제안된 알고리즘은 잠재적 유효 얼굴 요소들을 검출할 때까지 Viola & Jones의 객체 검출의 변수 값을 변화시켜 미 검출을 줄이고, 검출된 얼굴 요소의 크기, 위치, 유일성을 평가하는 검증을 이용해 중복 검출과 오 검출들을 제거시켜 준다. 시뮬레이션 결과들은 제안된 알고리즘이 검출된 객체들에 유효 얼굴 요소들을 포함시키고 나서 무효 얼굴 요소들을 제거하여 유효 얼굴 요소들만을 검출하는 것을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권6호
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• pp.647-666
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• 2009

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

• 전자공학회논문지B
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• 제29B권4호
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• pp.36-47
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• 1992

In this paper, a set of TM(template matching) mask using the AM(associative mapping) technique was generated and the edge detection algorithm for a SAR image was proposed. And also, the performance of the proposed edge detection algorithm was tested with the conventional edge detection techniques. The proposed edge detection algorithm created an edge image which was more accurate and clear than the conventional edge detection techniques and the performance of the proposed detection technique was not deteriorated for low intensity area in the image because the uncertainly thresholded value genetated by the conventional detection methods was requested. Also, the number of masks and the detection time were reduced by adjusting resolution of edge detection and the consideration for the threshold value extracting the edge was very intuitive.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.915-926
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• 2020

Outlier detection methods help one to identify unusual instances in data that may correspond to erroneous, exceptional, or surprising events or behaviors. This work studies conditional outlier detection, a special instance of the outlier detection problem, in the context of incorrect data label identification. Unlike conventional (unconditional) outlier detection methods that seek abnormalities across all data attributes, conditional outlier detection assumes data are given in pairs of input (condition) and output (response or label). Accordingly, the goal of conditional outlier detection is to identify incorrect or unusual output assignments considering their input as condition. As a solution to conditional outlier detection, this paper proposes the ratio-based outlier scoring (ROS) approach and its variant. The propose solutions work by adopting conventional outlier scores and are able to apply them to identify conditional outliers in data. Experiments on synthetic and real-world image datasets are conducted to demonstrate the benefits and advantages of the proposed approaches.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1283-1295
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• 2013

This study proposed an improvement in synchronously rotating reference frame-based voltage sag detection under distorted grid voltages. In the past, the conventional synchronously rotating reference frame (CSRRF)-based voltage sag detection was generally used in the voltage sag compensation applications. Its disadvantage is a long delay of detection time. The modified synchronously rotating reference frame (MSRRF)-based voltage sag detection is able to detect the voltage sag with only a short delay in detection time. However, its operation under distorted grid voltage conditions is unavailable. This paper proposed the improvement of modified synchronously rotating reference frame (IMSRRF)-based voltage sag detection for use in distorted grid voltages with very fast operation of voltage sag detection. The operation of the proposed voltage sag detections is investigated via simulations and experimentations to verify the performance of the IMSRRF-based voltage sag detection.

• The Journal of the Acoustical Society of Korea
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• 제22권3E호
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• pp.113-123
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• 2003

One of the most important problems in speech recognition is to detect the presence of speech in adverse environments. In other words, the accurate detection of speech boundary is critical to the performance of speech recognition. Furthermore the speech detection problem becomes severer when recognition systems are used over the telephone network, especially wireless network and noisy environment. Therefore this paper describes various speech detection algorithms for continuous digit recognition system used over wire/wireless telephone networks and we propose a algorithm in order to improve the robustness of speech detection using useful band selection under noisy telephone networks. In this paper, we compare some speech detection algorithms with the proposed one, and present experimental results done with various SNRs. The results show that the new algorithm outperforms the other speech detection methods.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.373-376
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• 2013

Nowadays, eyes detection is required and considered as the most important step in several applications, such as eye tracking, face identification and recognition, facial expression analysis and iris detection. This paper presents the eyes detection in facial images using Harris corner detection. Firstly, Haar-like features for face detection is used to detect a face region in an image. To separate the region of the eyes from a whole face region, the projection function is applied in this paper. At the last step, Harris corner detection is used to detect the eyes location. In experimental results, the eyes location on both grayscale and color facial images were detected accurately and effectively.

• 한국컴퓨터정보학회논문지
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• 제15권2호
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• pp.47-53
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• 2010

본 논문은 동영상에서 실시간 얼굴검출을 위하여 Residual Image 검출과 색상정보를 이용한 얼굴검출 기법을 제안하였다. 제안된 기법은 동영상에서 빠른 처리 속도와 높은 얼굴 검출율을 나타냈으며 기울어진 얼굴영상에 대한 보정작업을 통하여 검출 에러율을 줄였다. 실시간으로 전송된 동영상에서 검출의 대상이 되는 정지영상을 추출한다. 추출된 영상은 기울어진 얼굴검출을 위한 window회전 알고리즘을 사용하고 이렇게 보정된 영상은 얼굴 검출에 필요한 특징을 추출하기 위해 AdaBoost알고리즘을 사용하여 실시간으로 얼굴이 검출된 영상을 획득하게 된다.

• ETRI Journal
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• 제32권6호
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• pp.881-890
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• 2010

Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms; for example, a person smoking in a room may trigger a typical fire alarm system. In order to manage false alarms of conventional fire detection systems, a computer vision-based fire detection algorithm is proposed in this paper. The proposed fire detection algorithm consists of two main parts: fire color modeling and motion detection. The algorithm can be used in parallel with conventional fire detection systems to reduce false alarms. It can also be deployed as a stand-alone system to detect fire by using video frames acquired through a video acquisition device. A novel fire color model is developed in CIE $L^*a^*b^*$ color space to identify fire pixels. The proposed fire color model is tested with ten diverse video sequences including different types of fire. The experimental results are quite encouraging in terms of correctly classifying fire pixels according to color information only. The overall fire detection system's performance is tested over a benchmark fire video database, and its performance is compared with the state-of-the-art fire detection method.