Line segment detection of urban area in SAR images based on improved gray Hough transform

2005 ◽  
Author(s):  
Haiyang Wang ◽  
Xiaoyu Zhang ◽  
Baiyan ◽  
Delu Pan
1996 ◽  
Vol 27 (14) ◽  
pp. 45-54
Author(s):  
Kanji Tsukise ◽  
Ryoichi Fujiwara ◽  
Yoshiaki Tsuboi

2020 ◽  
Vol 98 ◽  
pp. 107034 ◽  
Author(s):  
Chenguang Liu ◽  
Rémy Abergel ◽  
Yann Gousseau ◽  
Florence Tupin

Author(s):  
ZHI-YONG LIU ◽  
HONG QIAO ◽  
LEI XU

By minimizing the mean square reconstruction error, multisets mixture learning (MML) provides a general approach for object detection in image. To calculate each sample reconstruction error, as the object template is represented by a set of contour points, the MML needs to inefficiently enumerate the distances between the sample and all the contour points. In this paper, we develop the line segment approximation (LSA) algorithm to calculate the reconstruction error, which is shown theoretically and experimentally to be more efficient than the enumeration method. It is also experimentally illustrated that the MML based algorithm has a better noise resistance ability than the generalized Hough transform (GHT) based counterpart.


2016 ◽  
Vol 20 (1) ◽  
pp. 82-88
Author(s):  
Chanho Lee ◽  
Ji-hyun Moon ◽  
Duy Phuong Nguyen

2015 ◽  
Vol 48 (12) ◽  
pp. 4012-4023 ◽  
Author(s):  
Zezhong Xu ◽  
Bok-Suk Shin ◽  
Reinhard Klette

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