Title :
Concentric circle detection based on normalized distance variance and the straight line Hough transform
Author :
Xing Chen ; Ling Lu ; Sheng Yang
Author_Institution :
Coll. of Electr. Eng. & Renewable Energy, China Three Gorges Univ., Yichang, China
Abstract :
Without any special qualifications, this paper proposed a novel method for concentric circles detection by using the geometrical characteristics of circle and the straight line Hough transform. A feature point neighborhood method and a normalized distance variance method are proposed to segment continuous curves and circles respectively for removing interference of noncircular objects which simplified the computation; Thirdly, circle centers and radius are detected by the straight line Hough transform. Because only two 2-dimensional voting are required for the circles detection, the proposed method avoided the problem of large storage which exists in the classical Hough transform and the detection efficiency is also enhanced. Finally, the concentric circles are identified and located according to the relation between the positions of circles. Experimental results demonstrate that, compared with the classical Hough transform, the proposed method improved execution efficiency greatly while maintaining high detection precision, it also offers good robustness in some complex images.
Keywords :
Hough transforms; geometry; object detection; concentric circle detection; feature point neighborhood method; geometrical characteristics; normalized distance variance method; straight line Hough transform; Computational efficiency; Computers; Image segmentation; Photonics; Transforms; Concentric circle; distance variance; normalization; resolutionratio; straight Hough transform;
Conference_Titel :
Computer Science & Education (ICCSE), 2014 9th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4799-2949-8
DOI :
10.1109/ICCSE.2014.6926565