A new edge-grouping algorithm for multiple complex objects localization

We present a new algorithm that provides an efficient localization method of elliptic industrial objects. Our proposed feature extraction inherits edge grouping approaches. But instead of utilizing edge linkage to restore incomplete contours, we introduce criteria of feature's parameters and optimize the criteria using an extended Kalman filter. Through a new parameter estimation under a proper ellipse representation, our system successfully generates ellipse hypotheses by grouping the fragmental edges in the scene. An important advantage of using our Kalman filter approach is that a desired feature can be robustly extracted regardless of ill-condition of partial edges and outlier noises. The experiment results demonstrate a robust localization performance.

[1]  Jean-Philippe Tarel,et al.  Curve finder combining perceptual grouping and a Kalman like fitting , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  David W. Jacobs,et al.  Robust and Efficient Detection of Salient Convex Groups , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Olivier Faugeras,et al.  Three-Dimensional Computer Vision , 1993 .

[4]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Peter K. Allen,et al.  Active, uncalibrated visual servoing , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[6]  Y. Motai,et al.  An interactive framework for acquiring vision models of 3-D objects from 2-D images , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Avinash C. Kak,et al.  Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties , 1992, CVGIP Image Underst..

[8]  Yuichi Motai,et al.  SmartView: hand-eye robotic calibration for active viewpoint generation and object grasping , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[9]  Edwin K. P. Chong,et al.  Efficient algorithms for finding the centers of conics and quadrics in noisy data , 1997, Pattern Recognit..

[10]  John Porrill.  Fitting ellipses and predicting confidence envelopes using a bias corrected Kalman filter , 1990, Image Vis. Comput..

[11]  Herbert Süße,et al.  Invariant Fitting of Planar Objects by Primitives , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Nobuyuki Fujiwara,et al.  Vision-based handling system using model-based vision and stereo ranging , 1998, 1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111).

[13]  Daniel P. Huttenlocher,et al.  Finding convex edge groupings in an image , 2004, International Journal of Computer Vision.

[14]  Clark F. Olson.  Improving the generalized Hough transform through imperfect grouping , 1998, Image Vis. Comput..

[15]  Yuichi Motai,et al.  Concatenate feature extraction for robust 3D elliptic object localization , 2004, SAC '04.