• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1003-1004
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• 2008

In this paper, we propose a 3D modeling method using Laser Slit Beam and Stereo Camera. We can get depth information of image by analyzing projected Laser Slit Beam on object. 3D modeling is demanded exquisite merge of 3D data. In our approach, we can get the depth image where the reliability is high. Each reconstructed 3D modeling is combined by the sink information which is acquired by SIFT (Scale Invariant Feature Transform) Algorithm. We perform experiments using indoor images. The results show that the proposed method works well in indoor environments

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2017년도 추계학술대회
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• pp.104-106
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• 2017

본 논문에서는 급부상하고 있는 가상현실 기술에서의 저작권 보호를 위해 VR영상을 타겟으로 하는 워터마킹 방법을 제안한다. 제안하는 방법은 VR영상의 합성에 널리 사용되는 SIFT 알고리즘을 통해 조건에 만족하는 점을 찾고, 그 점을 중심으로 한 주변 영역에 이산 웨이블릿 변환을 수행하여 워터마크를 삽입하는 방법이다. 또한 추출할 때에는 기존에 삽입한 워터마크와의 NCC값을 비교하여 일정 임계값 이상의 데이터들을 추출하고, 통계적 방법으로 최종 워터마크를 확정하게 된다. 이에 대해 가우시안 필터. 가우시안 노이즈, Sharpening, 회전변환, JPEG 압축 등의 공격을 가하고, 공격 후 추출되는 워터마크의 NCC, BER 값을 비교하여 워터마크의 강인성(robustness)을 확인한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.304-306
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• 2007

Methods of Object recognition from camera image are to compare features of color. edge or pattern with model in a general way. SIFT(scale-invariant feature transform) has good performance but that has high complexity of computation. Using simple color histogram has low complexity. but low performance. In this paper we represent a model as a color cooccurrence histogram. and we improve performance using pyramid matching. The color cooccurrence histogram keeps track of the number of pairs of certain colored pixels that occur at certain separation distances in image space. The color cooccurrence histogram adds geometric information to the normal color histogram. We suggest object recognition by pyramid matching of color cooccurrence histogram.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.6-8
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• 2007

In this paper, We propose reasoning system for object recognition and space classification using not only visual features but also contextual information. It is necessary to perceive object and classify space in real environments for mobile robot. especially vision based. Several visual features such as texture, SIFT. color are used for object recognition. Because of sensor uncertainty and object occlusion. there are many difficulties in vision-based perception. To show the validities of our reasoning system. experimental results will be illustrated. where object and space are inferred by bi -directional rules even with partial and uncertain information. And the system is combined with top-down and bottom-up approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1819-1820
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• 2008

Steel slabs are marked with slab management numbers (SMNs). To increase efficiency, automated identification of SMNs from digital images is desirable. Automatic extraction of SMNs is a prerequisite for automatic character segmentation and recognition. The images include complex background, and the position of the text region of the slabs is variable. This paper describes an pre-processing algorithm for detection of slab information using robust feature points extraction. Using SIFT(Scale Invariant Feature Transform) algorithm, we can reduce the search region for extraction of SMNs from the slab image.

• Asian Pacific Journal of Cancer Prevention
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• 제17권4호
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• pp.2199-2203
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• 2016

One of the most common cancer types faced by the women around the world is breast cancer. Among the several low, moderate and high penetrance genes conferring susceptibility to breast cancer, PTEN is one which is known to be mutated in many tumor types. In this study, we predicted and analyzed the impact of three deleterious coding non-synonymous single nucleotide polymorphisms rs121909218 (G129E), rs121909229 (R130Q) and rs57374291 (D107N) in the PTEN gene on the phenotype of breast tumors using computational tools SIFT, Polyphen-2, PROVEAN, MUPro, POPMusic and the GETAREA server.

• 한국자동차공학회논문집
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• 제22권3호
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• pp.68-74
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• 2014

As the number of ECUs (Electronic control units) are increasing, reliability and functional stability of a software in an ECU is getting more important. Therefore the application of functional safety standards ISO 26262 is making the software more reliable. Software fault injection test (SFIT) is required as a verification technique for the application of ISO 26262. In case of applying SFIT, an artificial error is injected to inspect the vulnerability of the system which is not easily detected during normal operation. In this paper, the basic concept of SFIT will be examined and the application of SIFT based on ISO26262 will be described.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.459-470
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• 2013

The discovery of nearest neighbors, without training in advance, has many applications, such as the formation of mosaic images, image matching, image retrieval and image stitching. When the quantity of data is huge and the number of dimensions is high, the efficient identification of a nearest neighbor (NN) is very important. This study proposes a variation of the KD-tree - the arbitrary KD-tree (KDA) - which is constructed without the need to evaluate variances. Multiple KDAs can be constructed efficiently and possess independent tree structures, when the amount of data is large. Upon testing, using extended synthetic databases and real-world SIFT data, this study concludes that the KDA method increases computational efficiency and produces satisfactory accuracy, when solving NN problems.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 하계학술대회
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• pp.407-408
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• 2012

최근 모바일환경에서 영상검색을 위한 연구가 활발히 진행됨에 따라 MPEG에서도 국제표준을 위한 연구가 진행되고 있다. 그러나 모바일의 제한된 성능환경과 외부적인 실외환경변화에 강인한 알고리즘개발이 시급하다. 따라서 본 논문에서는 다양한 환경변화에 강인한 영상검색 알고리즘을 개발하기 위하여 기존의 영상검색으로 많이 사용되고 있는 SIFT와 SURF 알고리즘의 성능을 분석하고자 한다. 실험에 사용된 데이터베이스는 MPEG에서 표준영상으로 채택된 ETRI dataset을 이용하였다. 실험결과， 기존의 알고리즘은 특징점 검출과 그 서술자가 서로 의존적임을 알 수 있었다.

• 로봇학회논문지
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• 제2권2호
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• pp.129-136
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• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.