Title :
Detection and Extraction of Discontinuous Lines
Author :
Wu, Zhanwei ; Kong, Bin ; Zheng, Fei ; Gao, Jun
Author_Institution :
Center for Biomimetic Sensing & Control Res. Inst. of Intell. Machine, Chinese Acad. of Sci., Hefei
Abstract :
A new algorithm for detecting and extracting discontinuous lines is presented against the shortcomings of the usual method for lines extraction. Firstly almost all of the line segments were acquired by the means of Hough transform, and then the line segments were grouped by the method of improved dynamic clustering algorithm. The improvement of the dynamic clustering algorithm are the initial cluster is based on the method of the standardized pattern transform and a kernel of every class replaces the centre of the class as the patterns of every class obey the norm distribution. In the next step the line segments belong to the same group are fitted into possible longer lines and the long lines´ existence is further defined by judging whether the total number of marginal points in the neighbourhood of the lines is large enough or not. At last, the redundant lines are also excluded by the means of dynamic clustering algorithm. Experiments demonstrate that the proposed algorithm is valid.
Keywords :
Hough transforms; feature extraction; pattern clustering; Hough transform; discontinuous lines detection; discontinuous lines extraction; dynamic clustering algorithm; initial cluster; line segments; norm distribution; standardized pattern transform; Biomimetics; Clustering algorithms; Equations; Heuristic algorithms; Image edge detection; Intelligent robots; Kernel; Machine intelligence; Robot sensing systems; Transforms; Discontinuity lines; Dynamic clustering algorithm; Hough transform; Lines fitting; Neighborhood edges detection;
Conference_Titel :
Robotics and Biomimetics, 2006. ROBIO '06. IEEE International Conference on
Conference_Location :
Kunming
Print_ISBN :
1-4244-0570-X
Electronic_ISBN :
1-4244-0571-8
DOI :
10.1109/ROBIO.2006.340263