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공간정보를 이용한 3차원 하천 경계선 매핑에 관한 연구
정윤재 ( Yun Jae Choung ),박현철 ( Hyen Cheol Park ),조명희 ( Myung Hee Jo ) 한국지리정보학회 2012 한국지리정보학회지 Vol.15 No.1
A river boundary is defined as the intersection between a main stream of a river and the land. Mapping of the river boundary is important for the protection of the properties in river areas, the prevention of flooding and the monitoring of the topographic changes in river areas. However, the utilization of the ground surveying technologies is not efficient for the mapping of the river boundary due to the irregular surfaces of river zones and the dynamic changes of water level of a river stream. Recently, the spatial information data sets such as the airborne LiDAR and aerial images are widely used for coastal mapping due to the acquisition of the topographic information without human accessibility. Due to these advantages, this research proposes a semi-automatic method for mapping of the river boundary using the spatial information data set such as the airborne LiDAR and the aerial photographs. Multiple image processing technologies such as the image segmentation algorithm and the edge detection algorithm are applied for the generation of the 3D river boundary using the aerial photographs and airborne topographic LiDAR data. Check points determined by the experienced expert are used for the measurement of the horizontal and vertical accuracy of the generated 3D river boundary. Statistical results show that the generated river boundary has a high accuracy in horizontal and vertical direction.
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Yu Liu,Jie Yang,Benzhen Guo,Jingjing Yang,Xiao Zhang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.2
With the fast development of industry and computer science technology, the image color recognition has been a hot topic. The prior research focus more on sensor and hardware based approaches which are not intelligent or convenient. In this paper, we present a novel image segmentation combined color recognition algorithm through boundary detection and deep neural network. The deep learning algorithm can largely increase the accuracy of classification whereas cut down the processing time consumed, we adopt the deep neural network and support vector machine to extract image features both in RGB and YUV color spaces. Boundary detection in sudden change, by contrast, is more global in nature, such as texture, so need to integrate the whole information of the image. Under the guidance, we modify the current segmentation methods with boundary detection technique to serve as the pre-processing step before classifying colors. Experimental results on synthetic and real images show that the new algorithm is effective and efficient, and is relatively independent of this type of noise. Further analysis is also conducted in the final section.
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에지정보에 적응적인 마스크를 이용한 시간방향 오류 은닉 방법
김용우,임찬,강현수,Kim Yong-Woo,Lim Chan,Kang Hyun-Soo 대한전자공학회 2005 電子工學會論文誌-SP (Signal processing) Vol.42 No.3
본 논문에서는 영상의 에지성분을 이용하여 손실된 프레임에서의 오류를 은닉하는 방법을 제안한다. 제안된 방법에서는 손실된 블록의 주변에 존재하는 상, 하, 좌, 우의 일정 부분을 에지 추출을 위한 영역으로 정의하고, 정의된 네 부분의 영역은 방향에 따라 선택적인 에지 연산자를 적용시켜 에지 성분을 추출한다. 이 에지정보는 영상이 복잡한 부분과 단순한 부분에 대해 복잡도를 결정하는 판단 기준이 되며 경계정합을 위한 마스크 폭을 조절하게 된다. 즉, 제시된 방법은 경계정합 수행시 정확도를 높이기 위하여 네 부분에서 추출된 에지성분의 양에 비례하여 방향에 따라 경계정합 마스크의 폭을 조절하고, 이에 따라 영상의 윤곽을 나타내는 에지 특성에 가중치를 적용함으로써, 개선된 움직임 벡터를 얻을 수 있도록 하였다. 기존의 방법들과 제안된 방법에 대한 오류은닉 결과를 비교함으로써 제안된 방법의 우수성 검증 및 장단점에 대해 분석한다. In this paper, we propose a temporal error concealment method based on the edge adaptive masking. In the method, four regions around the corrupted block - top, bottom, left, and right - are defined and the edge features of the regions are extracted by applying an edge operator for each direction. The size of a mask for the boundary matching is determined by the edge information, which can be considered as a criterion to measure the activity of the boundary region. In other words, it is determined such that the size of the mask is proportional to the amount of edge-component extracted from each region in order to yield the higher reliability on boundary matching. This process is equivalent to applying weights depending on the edge features, which leads the improved motion vector. In experiments, it is verified that the proposed method outperforms the conventional methods in terms of image quality, and then its merits and demerits are discussed.
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Applying Z-Curve Technique to Compute Skyline Set in Multi Criteria Decision Making System
T. Vijaya Saradhi,Kodukula Subrahmanyam,P. Venkateswara Rao,Hye-jin Kim 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.12
The skyline queries are the best tools to be used in distributed multi criteria decision making of web based applications for user commendations. However, as the Data dimensions are increasing size of dominance set and skyline set is also increasing. Increasing dimensionality becomes the major problem with real word databases. In skyline computation major cost depends on finding dominance tests between high dimensional objects and the order in which they are accessing. Space filling Z-curve is the best suitable way to address the challenges in skyline computation. In this proposed work, we incorporated Z-curve with optimized skyline boundary detection algorithm to effective access and early pruning. In this paper efficient hybrid index structure was proposed which takes the advantage of sorting and partition approaches to improve the storage and search efficiency. Experimental results show that our propose approach is better than the previous static skyline computation techniques in terms of searching and finding skyline set.
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