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	Efficient Clustering Aggregation Based on Data Fragments 期刊论文 OAI收割 IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2012, 卷号: 42, 期号: 3, 页码: 913-926 作者: Wu, Ou; Hu, Weiming; Maybank, Stephen J.; Zhu, Mingliang; Li, Bing 收藏 \| 浏览/下载：39/0 \| 提交时间：2015/08/12 Clustering aggregation comparison measure computational complexity data fragment fragment-based approach mutual information point-based approach
	Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割 6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.
	efficient clustering-based outlier detection algorithm for dynamic data stream 会议论文 OAI收割 5th International Conference on Fuzzy Systems and Knowledge Discovery, Jinan, PEOPLES R CHINA, OCT 18-20, Elahi Manzoor; Li Kun; Nisar Wasif; Lv Xinjie; Wang Hongan \| 收藏 \| 浏览/下载：17/0 \| 提交时间：2011/06/13 anomaly detection clustering based approach clustering-based outlier detection algorithm dynamic data stream data mining security of data
	A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Yao Z.-J. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However 3. applying the standard Hough transform equation to every point of the input image edge 4. according to the local threshold 6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes traditional Hough transform can only detect the lines 2. quantizing the parameter space and extracting a group of maximums according to the global threshold eliminating spurious peaks which are caused by the spreading effects and will improve the precision of tracking. cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately 5. fixing on the endpoints of the segments according to the dynamic clustering rule which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image parameter and line-segment spaces