• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.222-224
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• 1999

지문은 가장 효율적인 사용자 인증방법으로 이용되어져 왔다. 또한 컴퓨터의 발달과 더불어 자동지문 인식은 더욱 많이 연구되어졌고, 또한 급속도로 발전하였다. 이런 대부분의 연구들은 지문 인식에서 특징점 추출 및 정합부분에 관한 연구가 주류를 이루고 있다. 그런, 대단위 데이터베이스 검색 향상을 위한 방법의 연구는 아직도 미진한 실정이다. 본 연구는 기존의 지문 데이터베이스에 공간 인덱스를 추가시켜 지문을 효과적으로 추출하는 방법을 제시한다. 이 방법으로, 데이터베이스의 지문을 다차원공간 인덱스에 저장시킨다. 그리고, 지문을 검색을 할 때에는, 다차원공간상에서 미지 지문과 유사한 지문들을 추출하여, 후보지문을 만든다. 그리고, 매칭 작업은 이 후보지문들하고만 매칭 하여도 전체를 한 것과 같은 효과를 얻을 수 있다. 이러한 방법으로, 전체 지문 검색 시간을 단축시킬 수 있다.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1121-1135
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• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.609-616
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• 2017

National Geographic Information Institute has established a plan that preoccupies UCPs (Unified Control Points) at 2~3km intervals in urban areas by considering the distance between existing UCPs by satellite images and aerial photographs in 2015. In this study, we discussed the method of selecting the locations of optimal UCPs by simulating GPS reception environment in candidate sites for UCPs using GIS. For this purpose, we selected new candidate sites for installing UCPs using satellite images and aerial photographs, and analyzed the GPS reception environment by calculating the visibility distance from buildings around UCPs using GIS skyline analysis. The number of and the arrangement of visible satellites that are capable of GPS satellite reception from the viewpoint of sky view were showed by GIS skyline analysis. Quality evaluation results of GPS observation data were compared with average PDOP calculated from hourly PDOP and TEQC in two points of Sungkyunkwan University during 8 hours. As a result of GPS reception environment using GIS, if the PDOP increases, the data acquisition rate is lowed, and the multipath error and the cycle slip are increased. Thus, this study verified that the quality of GPS observation data can be secured by constructing three-dimensional spatial information and simulating PDOP when preoccupying multiple UCPs using GIS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.577-582
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• 2008

In this paper, we present a scheme to overcome the worst case complexity of the sphere decoder. If the number of visited nodes reaches the threshold, the detected symbol vector is determined between two candidate symbol vectors. One candidate symbol vector is obtained from the demodulated output of ZF receiver which is initial stage of the sphere decoder. The other candidate symbol vector consists of two sub-symbol vectors. The first sub-symbol vector consists of lately visited nodes running from the most upper layer. The second one contains corresponding demodulated outputs of ZF receiver. Between these two candidate symbol vectors, the one with smaller euclidean distance to the received symbol vector is chosen as detected symbol vector. In addition, we show the upper bound of symbol error rate performance for the sphere decoder using the proposed scheme. In the simulation, the proposed scheme shows the significant reduction of the worst case complexity while having negligible SER performance degradation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.9-12
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• 2015

In this paper, we propose a new feature matching algorithm by modifying and combining the FAST(Features from Accelerated Segment Test) feature detector and SURF feature descriptor which is robust to the distortion of the given image. Scale space is generated to consider the variation of the scale and determine the candidate of features in the image robust to the noise. The original FAST algorithm results in many feature points along edges. To solve this problem, we apply the principal curvatures for refining it. We also use SURF descriptor to make it robust against the variations in the image by rotation. Through the experiments, it is shown that the proposed algorithm has better performance than the conventional feature matching algorithms even though it has much less computational load. Especially, it shows a strength for noisy images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.11-18
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• 2005

To detect vehicles in image, first the image is transformed with the steerable pyramid which has independent directions and levels. Feature vectors are the collection of filter responses at different scales of a steerable image pyramid. For the detection of vehicles in image, feature vectors in feature points of the vehicle image is used. First the feature points are selected with the grid points in vehicle image that are evenly spaced, and second, the feature points are comer points which m selected by human, and last the feature points are corner Points which are selected in grid points. Next the feature vectors of the model vehicle image we compared the patch of the test images, and if the distance of the model and the patch of the test images is lower than the predefined threshold, the input patch is decided to a vehicle. In experiment, the total 11,191 vehicle images are captured at day(10,576) and night(624) in the two local roads. And the $92.0\%$ at day and $87.3\%$ at night detection rate is achieved.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.1-4
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• 2012

영상 매칭 기술은 컴퓨터 비전 분야에서 다양하게 응용될 수 있는 기초적인 기술 중에 하나이다. 대표적인 영상 매칭 기술인 SIFT나 SURF는 강인한 영상 매칭 성능을 나타내지만 계산량이 방대하여 실시간 기술에 사용될 수 없는 문제점을 가진다. 최근에 ORB나 BRISK는 FAST 특징점 검출기와 BRIEF 특징점 표현자를 조합하여 실시간 영상 매칭을 가능하게 하면서 기존의 영상 매칭 기술과 견줄만한 성능을 나타내었다. 본 논문에서는 FAST와 BRIEF를 수정하여 영상 왜곡에 강인하면서 실시간으로 매칭을 수행할 수 있는 영상 매칭 알고리즘을 제안한다. 노이즈에 강인하면서 스케일 변화를 고려하기 위하여 특징점 후보 영역을 제한하고 스케일 공간을 생성하여 특징점을 검출한다. 또한 영상의 회전 변화에 강인한 영상 매칭을 가능하게 하기 위하여 주변 픽셀 패턴의 Gradient로 특징점 방향을 결정하여 픽셀 밝기 값 비교로 이진 특징점 표현자를 생성한다. 제안하는 영상 매칭 알고리즘은 적은 계산량으로 기존의 알고리즘보다 우수한 영상 매칭 성능을 나타낸다. 특별히 노이즈가 존재하는 영상의 매칭에서 노이즈의 영향에 강인한 매칭 성능을 보여준다.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.67-73
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• 2005

Recently, the social requirement of personal identification techniques has been increasing. Fingerprint recognition is one of the biometries methods that has been widely used for this requirement. This paper proposes the fingerprint matching algorithm that uses the information of the ridge shapes of minutiae. In which, the data of the ridge shape are expressed in one-dimensional discrete-time signals. In our algorithm, we obtain one-dimensional discrete-time signals for ridge at every minutiae from input and registered fingerprints, and find pairs of minutia which have the similar ridge shape by comparing input fingerprint with registered fingerprint, thereafter we find candidates of rotation angle and moving displacement from the pairs of similar minutia, and obtain the final rotation angle and moving displacement value from those candidates set by using clustering method. After that, we align an input fingerprint by using obtained data, and calculate the matching rate by counting the number of corresponded pairs of minutia within the overlapped area of an input and registered fingerprints. As a result of experiment, false rejection rate(FRR) of $18.0\%$ at false acceptance rate(FAR) of $0.79\%$ is achieved.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.709-713
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• 2005

A new algorithm is proposed for the extraction of line segments to construct 3D wire-frame models of building from the high-resolution aerial images. The purpose of this study Is the accurate and effective extraction of line segments, considering the problems such as discordance of lines and blurred edges existing in the conventional methods. Using the edge map extracted from aerial images, chain code tracking of edges was performed. Then, we extract the line segments considering the strength of edges and the direction of them. SUSAN (Smallest Uni-value Segment Assimilating Nucleus) algorithm proposed by Smith was used to extract an edge map. The proposed algorithm consists of 4 steps: removal of the horizontal, vertical and diagonal components of edges to reduce non-candidate point of line segments based on the chain code tracking of the edge map, removal of contiguous points, removal of the same angle points, and the extraction of the start and end points to be line segments. By comparing the proposed algorithm with Boldt algorithm, better results were obtained regarding the extraction of the representative line segments of buildings, having relatively less extraction of unnecessary line segments.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.176-190
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• 2002

According as vehicles increases, system such as Advanced Drivers Assistance System(ADAS ) to inform forward situation to driver is required. In this paper, we proposes method to detect forward vehicles and lane from sequential color images by basis process to inform forward situation to driver. We detect a front vehicle using that shadow area exists on part under vehicles and that road area occupies many parts even if road traffic is confused. We detect lane information using that lane part is white order by reverse characteristic of shadow area. This method shows good result in case road is confused or there is direction indication to road. HSV color space is selected for color modeling. This method uses saturation component and value component in HSV color model to detect vehicles and lane. It uses statistics features of HSV component and position to know whether detected vehicles area is vehicles such as vehicles previous frame. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and Present the results such as processing time, accuracy and vehicles detection against the images.