
For FullText PDF, please login, if you are a member of IEICE,
or go to Pay Per View on menu list, if you are a nonmember of IEICE.

Circle Detection Based on Voting for Maximum Compatibility
Yuanqi SU Yuehu LIU Xiao HUANG
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E95D
No.6
pp.16361645 Publication Date: 2012/06/01
Online ISSN: 17451361
DOI: 10.1587/transinf.E95.D.1636
Print ISSN: 09168532 Type of Manuscript: PAPER Category: Image Recognition, Computer Vision Keyword: Hough transform, circle detection, voting, truncating operation, oriented chamfer distance,
Full Text: PDF>>
Summary:
We present a fast voting scheme for localizing circular objects among clutter and occlusion. Typical solutions for the problem are based on Hough transform that evaluates an instance of circle by counting the number of edge points along its boundary. The evaluated value is proportional to radius, making the normalization with respect to the factor necessary for detecting circles with different radii. By representing circle with a number of sampled points, we get rid of the step. To evaluate an instance then involves obtaining the same number of edge points, each close to a sampled point in both spatial position and orientation. The closeness is measured by compatibility function, where a truncating operation is used to suppress noise and deal with occlusion. To evaluate all instances of circle is fulfilled by letting edge point vote in a maximizing way such that any instance possesses a set of maximally compatible edge points. The voting process is further separated into the radiusindependent and dependent parts. The timeconsuming independent part can be shared by different radii and outputs the sparse matrices. The radiusdependent part shifts these sparse matrices according to the radius. We present precisionrecall curves showing that the proposed approach outperforms the solutions based on Hough transform, at the same time, achieves the comparable time complexity as algorithm of Hough transform using 2D accumulator array.

