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| A Randomized Corner Detection Algorithm |
| L Na, FENG Zu-Ren |
| State Key Laboratory for Manufacturing Systems Engineering, Systems Engineering Institute, Xian Jiaotong University, Xian 710049 |
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Abstract There is no parametric formulation of corner feature. Therefore, the conventional Hough transform can not be employed to transform the corner detection into maximum search in parametric space. A randomized Hough transform in Monte Carlo framework is presented, which detects the corner by searching for the local maximum in the intersection point cumulative space instead of parametric space. The intersection point cumulative space is a concept based on the fact that the corner is the intersection point of two lines. The proposed algorithm is demonstrated and the computing procedures are given. The proposed algorithm is isotropic, robust to image rotation, insensitive to noise and not susceptible to diagonal edge. Experimental results show that it outperforms Harris detector, Shen Wang algorithm, and SIFT feature detection algorithm.
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Received: 15 March 2010
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2011, Vol. 24 
