Comparative research on two methods of straight line extraction based on sub-pixel

Author(s):  
Gongqiang Cui ◽  
xiaofei wang ◽  
Hua Fan
Author(s):  
Shenghua Xu ◽  
Jiping Liu ◽  
Jianping Pan ◽  
Yong Wang

2011 ◽  
Vol 32 (23) ◽  
pp. 8315-8330 ◽  
Author(s):  
Shenghua Xu ◽  
Jiping Liu ◽  
Yong Wang ◽  
Litao Han ◽  
Yunsheng Zhang

2013 ◽  
Vol 734-737 ◽  
pp. 3079-3084
Author(s):  
Yin Wen Dong ◽  
Luan Wan ◽  
Zhao Ming Shi ◽  
Jing Xin An

Aiming at anhydrous bridge automatically identification in aerial images, an anhydrous bridge recognition algorithm based on the geometric characteristics is proposed. Firstly, the original image is do threshold segmentation to get binary image. Secondly, binary image is do morphological processed to get bridge area enhanced image and bridge area corrosion image, and these two bridge area are subtracted to extract suspected bridge area based on bridge rectangle feature. Finally, bridge regional area is positioned according to the straight-line characteristics of the bridge. Experimental results show the proposed algorithm can accurately identify the anhydrous bridge effectively. Key words: aerial image; anhydrous bridges identification; edge detection ; straight line extraction ; geometric features


Author(s):  
Feng-juan Liu

In order to apply the K-means algorithm to the quantitative evaluation model of interactive whiteboard class, the automatic correction method of the natural scene text plane image in the interactive whiteboard class is put forward. This method makes full use of the whiteboard border line information, and completes the whiteboard correction through the Canny operator edge detection, the PPHT straight line extraction, the K-means algorithm linear clustering, H matrix transformation and other steps. Finally, experiments are carried out to test the performance of the algorithm. The research results show that the algorithm has a high success rate of correction for basic simple background and simple content whiteboard, and the algorithm performance is relatively stable. It can be seen that the K-means algorithm has broad application prospects in the quantitative evaluation model of interactive whiteboard classroom.


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