• 반도체디스플레이기술학회지
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• 제7권3호
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• pp.59-63
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• 2008

Geo-coding refers to the process of associating data with location information, and the system deals with geographic identifiers expressed as latitude and longitude or street addresses. Although many services have been launched, there still remains a problem for users to create geo-coded photo with manually labeling GPS(Global Positioning System) coordinate or synchronizing with separate devices. In this paper, we design and implement a geo-coding system which utilizes the time and location information embedded in digital photographs in order to automatically categorize a personal photo collection. An included GPS receiver labels a photograph with its corresponding GPS coordinates, and the position of the camera is automatically recorded into the photo image header at the moment of capture. The place and time where the photo was taken allows us to provide context metadata on the management and retrieval of information.

• International Journal of Advanced Culture Technology
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• 제9권4호
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• 방송공학회논문지
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• 제7권2호
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• pp.126-135
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• 2002

영상은 색상, 형태, 위치, 질감 같은 다양한 특성을 갖고 있기 때문에 하나의 특성만을 이용하여 일괄적으로 영상을 검색할 경우, 만족할 만한 검색효율을 얻기가 어렵다. 특히, 대용량의 영상 데이터베이스일수록 그 같은 현상은 빈번하게 일어나기 때문에 기존의 내용 기반 영상 검색 시스템들은 대부분 하나 이상의 특성을 이용하여 검색효율 향상을 죄하고 있다. 본 논문에서는 Centroid 위치벡터를 이용하여 영상 내의 색상 정보뿐만 아니라, 특정 색상에 대한 위치정보를 고려하는 기법을 제안한다. 질의영상의 한 색상에 대해 Centroid 위치벡터를 추출하고 비교영상의 같은 색상의 Centroid 위치벡터와의 거리를 비교하여 그 거리가 짧을수록 각 색상의 위치 유사도를 높게 책정하는 방식을 제안한다. 제안된 검색 기법은 기존의 색상 분포만을 이용하는 검색 기법에 비해, 원근 처리된 영상에 강인하고, 회전되거나 뒤집힌 영상의 변별력이 향상되었다. 또한, 제안된 방식은 색상정보와 위치정보의 추출을 이원화시키지 않고 동시에 추출함으로써 계산량을 줄이고, 효율적인 색인 파일을 생성하여 검색속도를 향상시켰다.

• 제어로봇시스템학회논문지
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• 제22권8호
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• pp.597-602
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• 2016

In image guided surgery, a patient registration process is a critical process for the successful operation, which is required to use pre-operative images such as CT and MRI during operation. Though several patient registration methods have been studied, we concentrate on one method that utilizes 3D surface measurement data in this paper. First, a hand-held 3D surface measurement device measures the surface of the patient, and secondly this data is matched with CT or MRI data using optimization algorithms. However, generally used ICP algorithm is very slow without a proper initial location and also suffers from local minimum problem. Usually, this problem is solved by manually providing the proper initial location before performing ICP. But, it has a disadvantage that an experience user has to perform the method and also takes a long time. In this paper, we propose a method that can accurately find the proper initial location automatically. The proposed method finds the proper initial location for ICP by converting 3D data to 2D curvature images and performing image matching. Curvature features are robust to the rotation, translation, and even some deformation. Also, the proposed method is faster than traditional methods because it performs 2D image matching instead of 3D point cloud matching.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.610-615
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• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• 한국대기환경학회지
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• 제31권6호
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• pp.585-592
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• 2015

In this study, by applying mobile based GIS and image analysis of particulate matter ($PM_{10}$) concentration in Seoul and Ulsan in Korea, to identify the user's location and also implemented the application to information exchange. It strengthened citizens' access to air quality information through the application and derived the expanded environment information sharing through real-time user participation. Through atmospheric concentrations image analysis, it showed a new environmental information construction possibility. It had the effect of expanding the information collecting through the local user participation on the limited information collected area which place is not yet constructed atmospheric monitoring network. Location-based particulate matter information service application provides a user location's $PM_{10}$ information from the 25 urban air monitoring network real-time database of the Ministry of Environment. Furthermore, if the user sent a picture of the atmosphere to the server, should match the image density values of the database and express on Seoul's maps through the IDW interpolation. And then a $PM_{10}$ concentration result is transmitted to user in real time.

• 한국컴퓨터정보학회논문지
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• 제14권12호
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• pp.89-96
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• 2009

이미지나 동영상은 텍스트보다도 많은 정보를 함축하고 있기 때문에 이를 추출해내고 분석하는 일은 매우 중요한 일이 되고 있다. 본 연구에서는 동영상에서 사람의 얼굴을 검출하고, 눈의 영역이 확인된 이미지를 이용하여 눈의 개폐와 눈동자의 위치를 판단하는 방법을 제시하였다. 색상을 흑백으로 양극화하고 수평화하여 이미지를 정규화한 후, 눈가의 수평, 수직의 모서리 점들을 파악하여 측정치를 얻어낸다. 이를 통하여 눈의 개폐와 눈동자의 위치를 판단한다. 동영상에서 얻어낸 임의의 52개의 눈 이미지를 실험대상으로 처리하여 눈의 개폐를 98% 검출하고 95%의 정확도로 눈동자 위치를 판단하는 실험결과를 얻었다.

• 지능정보연구
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• 제21권2호
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• pp.113-129
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• 2015

장소 브랜딩은 특정 장소에 대한 의미 부여를 통해 장소성의 정체성 및 공동가치를 생성하며 가치 창출을 하는데 중요한 활동이며, 장소 브랜드에 대한 이미지 파악을 통해 이루어진다. 이에 마케팅, 건축학, 도시건설학 등 여러 분야에서는 인상적인 장소 브랜드의 이미지를 구축하기 위하여 많은 노력을 기울이고 있다. 하지만 설문조사를 포함한 대면조사 방법은 대부분 주관적인 작업이며 측정에 많은 인력 또는 고도의 전문 인력이 소요되어 고비용을 발생시키므로 보다 객관적이면서도 비용효과적인 브랜드 이미지 조사 방법이 필요하다. 이에 본 논문은 텍스트마이닝을 통하여 장소 브랜드의 이미지 강도를 객관적이고 저비용으로 얻는 방법을 찾는 것을 목적으로 한다. 제안하는 방법은 장소 브랜드 이미지를 구성하고 있는 요인과 그 키워드들을 관련 웹문서에서 추출하며, 추출된 정보를 통해 특정 장소의 브랜드 이미지 강도를 측정하는 방법이다. 성능은 안홀트 방법에서 평가에 사용하는 전세계 50개 도시 이미지 인덱스 순위와의 일치도로 검증하였다. 성능 비교를 위해 임의로 순위를 매기는 방법, 안홀트의 설문방식대로 일반인이 평가하는 방법, 본 논문의 방법을 사용하되 안홀트의 방법으로 학습한 것으로 유의한 것으로 추정되는 평가 항목만을 반영하는 방법과 비교하였다. 그 결과 제안된 방법론은 정확성, 비용효율성, 적시성, 확장성, 그리고 신뢰성 측면에서 우수함을 보일 수 있었다. 따라서 본 연구에서 제안한 방법론은 안홀트 방식에 상호 보완적으로 사용될 수 있을 것이다. 향후에는 장소 브랜드 이미지를 형성하는 속성 별로 등장횟수를 계산 한 후에 장소 브랜드에 대한 태도, 연상, 그리고 브랜드 자산과의 인과관계를 자동으로 파악할 수 있는 부분까지 구현하고 실증적 실험을 할 예정이다.

• 한국측량학회지
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• 제32권3호
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• pp.217-223
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• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• 한국측량학회지
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• 제37권5호
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.