• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.355-362
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• 2017

Recently, UAV(Unmanned Aerial Vehicle) have been utilized in various fields, including surveys, mapping, and spatial analysis, depending on the increase in demand for spatial information and UAV is receiving a lot of attention due to rapid data acquisition and economic viability. In this study, the applicability of UAV image images was analyzed for urban disaster prevention. UAV images were acquired for the study area and digital surface model and ortho image were generated through data processing. Also, the process using PPK(Post Processed Kinematic) GNSS method is compared with existing method. Through the research, it was able to effectively deploy urban disaster prevention information about the target area, and displayed the effectiveness of the methods for efficient comparison with existing unmanned aerial photogrammetry. If the PPK technique is applied to thethe disaster prevention field, it is expected that the work flow in the field of rapid data acquisition and disaster prevention data construction can be greatly improved.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.2
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• pp.87-93
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• 1989

Squared-error Pattern Clustering algorithm used in unsupervised pattern recognition and image processing application demands substantial processing time for operation of feature vector matrix. So, this paper propose the fast squared-error Pattern Clustering Processor using the Residue Number System which have been the nature of parallel processing and pipeline. The proposed Squared-error Pattern Clustering Processor illustrate satisfiable error rate for Cluster number which can be divide meaningful region and about 200 times faster than 80287 coprocessor from experiments result of image segmentation. In this result, it is useful to real-time processing application for large data.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.59-64
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• 2002

컴퓨터 그래픽스 기술과 H/W의 발달로 3D GIS에 대한 연구가 활발히 진행되고 있다. 최근 3D GIS에 대한 활발한 연구 중 3D 가상도시의 구축이 중요한 연구로 떠오르고 있다. 3D 가상도시는 국방, 교통, 통신, 지적, 지하시설물, 관광, 도시계획, 도시모델링 등에 다양하게 활용될 수 있다. 현재 우리나라에서 3D 가상도시의 구축은 미약하지만 앞으로 그 수요는 더욱 더 많아질 것이다. 3D 가상도시의 구축에는 GIS, 컴퓨터 그래픽스, Database, 자료구조, 3D 모델링 등의 다양한 기술이 필요하다. 3D 가상도시의 구축의 방법은 크게 1/1,000수치지도+실제측량, 1/1,000수치지도+입체 인공위성 영상+수치사진측량, 1/1,000수치지도+항공사진측량 도화원도, 1/1,000수치지도+항공레이저스캐닝의 방법을 적용해 볼 수 있다. 현재 우리나라 여건상 첫 번째 방법이 가장 일반적으로 사용이 되나 도화원도에 대한 규제를 완화하여 세 번째 방법을 적용하는 것이 가장 효과적일 것이다. 3D 가상도시는 인터넷 기술과 접목이 되어 3D Web GIS의 형태로 앞으로의 GIS 주류를 이룰 것이다. 그러나 국내에서 3D 가상도시의 구축에 관한 연구는 미약한 수준이다. 3D 자료취득, 자료처리, 모델링 부문에 대한 연구가 시급하다.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.325-335
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• 1996

Visual features are crucial for monitoring the growth state, indexing the drying performance, and grading the quality of oak mushrooms. A computer vision system with neural net information processing technique was utilized to quantize quality factors of a dried oak mushrooms distributed over the cap and gill sides. In this paper, visual feature extraction algorithm were integrated with the neural net processing to deal with various fuzzy patterns of mushroom shapes and to compensate the fault sensitiveness of the crisp criteria and heuristic rules derived from the image processing results. The proposed algorithm improved the segmentation of the skin features of each side, the identification of cap and gill surfaces, the identification of stipe states and removal of the stipe, etc. And the visual characteristics of dried oak mushrooms were analyzed and primary visual features essential to tile quality evaluation were extracted and quantized. In this study, black and white gray images were captured and used for the algorithm development.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.378-391
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• 2010

In this paper, it is tested that an individual is able to be identified with finger face images and the results are presented. Special operators, FFG(Facet Function Gradient) masks by which the gradient of a facet function fit on a gray levels of image patches can be computed are used and a new procedure named F-algorithm is introduced to match the finger face images. The finger face image is divided into the equal subregions and each subregions are divided into equal patches with this algorithm. The FFG masks are used for convolution operation over each patch to produce scalar values. These values from a feature matrix, and the identity of fingers is determined by a norm of the elements of the feature matrices. The distribution of the norms shows conspicuous differences between the pairs of hand images of the same persons and the pairs of the different persons. This is a result to prove the ability of discrimination with the finger face image. An identification rate of 95.0% is obtained as a result of the test in which 500 hand images taken from 100 persons are processed through F-algorithm. It is affirmed that the finger face reveals to be such a good biometrics as other hand parts owing to the ability of discrimination and the identification rate.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.337-339
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• 2001

본 연구에서는 임상적으로 얻어진 95개의 영상 자료를 전산화하여 특정 간 영역의 명도분포를 분석하여 이와 간의 지방화 정도와의 상관성을 연구하였다. 지방화 정도를 판단하는 임상적 기준으로 보편적으로 인정되는 지방간지수와 계산된 평균 명도 수치와의 선형 상관 계수를 구하였다. 각각의 영상의 밝기 및 에코정도가 일반적으로 불균일하기 때문에 이를 보정하기 위해 밝은 명도와 어두운 명도의 기준영역을 선정하여 상대명도를 추출하였다. 두 가지 독립적인 방법으로 기준 영역을 선택하여 비교한 결과, 임상 지방간지수와 높은 상관성을 보임을 알 수 있었고, 지방간 진단의 보조자료로 유용함을 확인하였다. 계산된 지방간지수와 상대명도의 상관계수는 0.69 에서 0.79로 나타났다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.60-64
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• 2011

In this paper, we propose a new post-processing technique that removes blocking and ringing artifacts in Block discrete cosine transformation (BDCT)-coded images using bilateral filtering. The selection of filter parameters is a key issue in the application of a bilateral filter because it significantly affects the result. An efficient method of selecting the bilateral filter parameters is presented. The experimental results show that the proposed approach alleviates the artifacts efficiently in terms of PSNR, MSDS, and SSIM.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.416-421
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• 2008

This paper realizes a system that recognizes traffic safety signs by applying the principle used for game in reverse. The game used for this paper is one that expresses the shape of temporary objects intended by the maker when the maker sees the numerical image provided on (x, y) coordinates and then expresses it on the mesh. After separating the traffic safety sign image from the input image, the system is realized by outputting the content of the sign into letters by recognizing the forms and colors constituting the sign using the puzzle game above. Our system has fast process time and better rate of recognition than the existing system with black-and-white image processing and recognition without any penciling progress.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.405-416
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• 2019

Due to the development of information and communication technology, the production and processing speed of data is getting faster. To classify objects using machine learning, which is a field of artificial intelligence, data required for training can be easily collected due to the development of internet and geospatial information technology. In the field of geospatial information, machine learning is also being applied to classify or recognize objects using images and point clouds. In this study, the problem of manually constructing training data using existing digital map version 1.0 was improved, and the technique of classifying roads, buildings and vegetation using image and point clouds were proposed. Through experiments, it was possible to classify roads, buildings, and vegetation that could clearly distinguish colors when using true ortho-image with only RGB (Red, Green, Blue) bands. However, if the colors of the objects to be classified are similar, it was possible to identify the limitations of poor classification of the objects. To improve the limitations, random forest and support vector machine techniques were applied after band fusion of true ortho-image and normalized digital surface model, and roads, buildings, and vegetation were classified with more than 85% accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.161-168
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• 2010

This study aims to propose a method that shall rapidly acquire 3D information of the fast and frequently changing city areas by using the images taken by the UAV photogrammetric method, and to develop the process of the acquired data. For this study's proposed UAV photogrammetric method, low-cost UAV and non-metric digital camera were used. The elements of interior orientation were acquired through camera calibration. The artificial 3D model of the artificial structures was constructed using the image data photographed at the target area and the results of the ground control point survey. The digital surface model was created for areas that were changed due to a number of civil works. This study also analyzes the proposed method's application possibility by comparing a 1/1,000 scale digital map and the results of the ground control point survey. Through the above studies, the possibilities of constructing a 3D virtual city model renewal of 3D GIS database, abstraction of changed information in geographic features and on-demand updating of the digital map were suggested.