• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.616-626
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial feature information and the face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by combining the multiple frequency domains for each depth image and depth fusion using fuzzy integral. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. It is used as the reference point to normalize for orientated facial pose and extract multiple areas by the depth threshold values. In the second step, we adopt as features for the authentication problem the wavelet coefficient extracted from some wavelet subband to use feature information. The third step of approach concerns the application of eigenface and Linear Discriminant Analysis (LDA) method to reduce the dimension and classify. In the last step, the aggregation of the individual classifiers using the fuzzy integral is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) show the highest recognition rate among the regions, and the depth fusion method achieves 98.6% recognition rate, incase of fuzzy integral.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.103-116
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• 2017

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner, which can derive new qualitative spatial knowledge representing both topological and directional relationships between two arbitrary spatial objects in efficient way using Aparch Spark SQL. Apache Spark SQL is well known as a distributed parallel programming environment which provides both efficient join operations and query processing functions over a variety of data in Hadoop cluster computer systems. In our spatial reasoner, the overall reasoning process is divided into 6 jobs such as knowledge encoding, inverse reasoning, equal reasoning, transitive reasoning, relation refining, knowledge decoding, and then the execution order over the reasoning jobs is determined in consideration of both logical causal relationships and computational efficiency. The knowledge encoding job reduces the size of knowledge base to reason over by transforming the input knowledge of XML/RDF form into one of more precise form. Repeat of the transitive reasoning job and the relation refining job usually consumes most of computational time and storage for the overall reasoning process. In order to improve the jobs, our reasoner finds out the minimal disjunctive relations for qualitative spatial reasoning, and then, based upon them, it not only reduces the composition table to be used for the transitive reasoning job, but also optimizes the relation refining job. Through experiments using a large-scale benchmarking spatial knowledge base, the proposed reasoner showed high performance and scalability.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.157-168
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• 2010

A terrain is an essential element for constructing a virtual world in which game characters and objects make various interactions with one another. Creating a terrain requires a great deal of time and repetitive editing processes. This paper presents a 3D terrain reconstruction system to create 3D terrain in virtual space based on real terrain data. In this system, it converts the coordinate system of the height maps which are generated from a stereo camera and a laser scanner from global GPS into 3D world using the x and z axis vectors of the global GPS coordinate system. It calculates the movement vectors and the rotation matrices frame by frame. Terrain meshes are dynamically generated and rendered in the virtual areas which are represented in an undirected graph. The rendering meshes are exactly created and updated by correcting terrain data errors. In our experiments, the FPS of the system was regularly checked until the terrain was reconstructed by our system, and the visualization quality of the terrain was reviewed. As a result, our system shows that it has 3 times higher FPS than other terrain management systems with Quadtree for small area, improves 40% than others for large area. The visualization of terrain data maintains the same shape as the contour of real terrain. This system could be used for the terrain system of realtime 3D games to generate terrain on real time, and for the terrain design work of CG Movies.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.80-91
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• 2010

As the volume of image data increases dramatically, its good organization of image data is crucial for efficient image retrieval. Clustering is a typical way of organizing image data. However, traditional clustering methods have a difficulty of requiring a user to provide the number of clusters as a parameter before clustering. In this paper, we discuss an approach for clustering image data that does not require the parameter. Basically, the proposed approach is based on Cross-Association that finds a structure or patterns hidden in data using the relationship between individual objects. In order to apply Cross-Association to clustering of image data, we convert the image data into a graph first. Then, we perform Cross-Association on the graph thus obtained and interpret the results in the clustering perspective. We also propose the method of hierarchical clustering and the method of outlier detection based on Cross-Association. By performing a series of experiments, we verify the effectiveness of the proposed approach. Finally, we discuss the finding of a good value of k used in k-nearest neighbor search and also compare the clustering results with symmetric and asymmetric ways used in building a graph.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.481-494
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• 2008

In this paper we propose Fourier magnitudes based privacy preserving clustering on time-series data. The previous privacy-preserving method, called DFT coefficient method, has a critical problem in privacy-preservation itself since the original time-series data may be reconstructed from privacy-preserved data. In contrast, the proposed DFT magnitude method has an excellent characteristic that reconstructing the original data is almost impossible since it uses only DFT magnitudes except DFT phases. In this paper, we first explain why the reconstruction is easy in the DFT coefficient method, and why it is difficult in the DFT magnitude method. We then propose a notion of distance-order preservation which can be used both in estimating clustering accuracy and in selecting DFT magnitudes. Degree of distance-order preservation means how many time-series preserve their relative distance orders before and after privacy-preserving. Using this degree of distance-order preservation we present greedy strategies for selecting magnitudes in the DFT magnitude method. That is, those greedy strategies select DFT magnitudes to maximize the degree of distance-order preservation, and eventually we can achieve the relatively high clustering accuracy in the DFT magnitude method. Finally, we empirically show that the degree of distance-order preservation is an excellent measure that well reflects the clustering accuracy. In addition, experimental results show that our greedy strategies of the DFT magnitude method are comparable with the DFT coefficient method in the clustering accuracy. These results indicate that, compared with the DFT coefficient method, our DFT magnitude method provides the excellent degree of privacy-preservation as well as the comparable clustering accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Journal of Navigation and Port Research
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• v.30 no.8 s.114
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• pp.623-629
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• 2006

Recently, bemuse of extensive use of hydrographic information, interoperability of Marine Geographic products is very important for efficient use of geographic information systems. Open GIS Consortium(OGC) developed the Open Geodata Interoperability Specification(OpenGIS) to support the interoperability in the distributed environment, especially Geography Markup Language(GML) Implementation Specification. Geography Markup Language is an XML grammar written in XML Schema for the modelling, transporting, and storing of geographic information GML provides a variety of objects for describing geography including features, coordinate reference systems, geometry, topology, time, units of measure and generalized values. S-57 is currently the IHO standard for the exchange of digital hydrographic data. To date, it ms been used almost exclusively for encoding Electronic Navigational Charts(ENCs). Even though, S-57 is intended to support all types of hydrographic data. In order to meet this requirement, a new standard is being developed. GML will be the core encoding rule of IHO's new standard. But there has been no study that tried to develop the GML for ENC that are recognized as base mop in the Marine GIS. This paper presents the process and results on development of application schema for converting ENC into GML.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.97-107
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• 2009

In image-based gait recognition systems, physical factors, such as the camera angle and the lens distortion, and environmental factors such as illumination determines the performance of recognition. In this paper we present a robust gait recognition method by compensating various types of image distortions. The proposed method is compared with existing gait recognition algorithm with consideration of both physical and environmental distortion factors in the input image. More specifically, we first present an efficient compensation algorithm of image distortion by using the projective transform, and test the feasibility of the proposed algorithm by comparing the recognition performances with and without the compensation process. Proposed method gives universal gait data which is invariant to both distance and environment. Gained data improved gait recognition rate about 41.5% in indoor image and about 55.5% in outdoor image. Proposed method can be used effectively in database(DB) construction, searching and tracking of specific objects.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.166-171
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• 2000

밀티빔 음향 측심기 (Multibeam Echo Sounder)는 탐사선에 수직방향으로 해저면을 주사(Swath)하여, 한번의 송수신(Ping)으로 다중의 빔자료를 얻을 수 있는 측심기로, 해저면에 반사되어 되돌아오는 음파의 음압을 기록하고, 사이드 스캔 소나 자료도 동시에 취득하는 기능을 가지고 있으므로, 측심된 해저 지형(Bathymetry)과 해저 지형을 덮고 있는 해저면의 퇴적 상황(Sediment Environment)도 동시에 얻을 수 있는 다목적 측심기이다. 본 논문에서는 L3사의 Sea Beam 2100 멀티빔 음향 측심기를 통해 얻은 자료를 처리하여, 3차원 공간 데이터인 DEM(Digital Elevation Model)을 생성하고, VRML을 이용한 웹상에서의 해저 지형 가시화를 통해, 세계 어느 곳에서나 웹을 통하여 쉽게 정보를 공유할 수 있는 3차원 해저 지리 정보 시스템의 구현을 목적으로 한다. 멀티빔 음향 측심기를 통해 얻어진 자료는 항해 자료 보정, 음속 보정, 빔 좌표 계산과 분리, 오측심 자료 제거, 조석 보정 등의 단계를 거쳐 측심자료의 정확도 및 신뢰도를 높이는 과정을 거치게 된다. 보정된 멀티빔 음향 측심자료는 무작위 점 사상(Point Topology)으로 산재 되어 있는 빔 자료를 임의의 단위영역으로 변환하는 과정을 거쳐야 하는데, 이 과정을 격자화라고 한다. 자료의 격자화를 통해 3차원 공강 데이터인 DEM 파일을 제작하고, 이 DEM 파일과 음압 영상을 이용해 웹상에서의 3차원 해저 지형의 가시화를 실현한다. 웹상에서의 3차원 지형 가시화에서 방대한 양의 지형 데이터는 데이터 전송 시간과 렌더링 시간에 치명적인 문제이다. 따라서, 렌더링 시간과 데이터 전송 시간을 단축시키기 위한, 지형 자료의 LOD(Level of Detail)를 통해, VRML을 이용한 보다 효과적인 웹상에서의 3차원 해저 지형의 가시화를 실현한다.면 기업은 고객으로 공간적인 제약으로 인한 불신을 불식시키는 신뢰감을 주게 된다. 이러한 고객서비스 향상과 물류비용 절감은 사이버 쇼핑몰이 전국 어디서나 우리의 안방에서 자연스럽게 점할 수 있는 상황을 만들 것이다.SP가 도입되어, 설계업무를 지원하기위한 기본적인 시스템 구조를 구상하게 된다. 이와 함께 IT Model을 구성하게 되는데, 객체지향적 접근 방법으로 Model을 생성하고 UML(Unified Modeling Language)을 Tool로 사용한다. 단계 4)는 Software Engineering 관점으로 접근한다. 이는 최종산물이라고 볼 수 있는 설계업무 지원 시스템을 Design하는 과정으로, 시스템에 사용될 데이터를 Design하는 과정과, 데이터를 기반으로 한 기능을 Design하는 과정으로 나눈다. 이를 통해 생성된 Model에 따라 최종적으로 Coding을 통하여 실제 시스템을 구축하게 된다.the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technological effects. Since the HAN projects consists of 18 subprograms, it is difficult In evaluate all the subprograms simultaneously. Despite, each program is being performed under the category of HAN projects, so the common soci

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.