Circle object recognition based on monocular vision for home security robot

In this paper, a circle object recognition method based on monocular vision for the home security robots is proposed. This vision system is able to process image and recognize a colored ball rapidly. The proposed method consists of two submodules, which are the object segmentation module and the circle detection module. In order to implement the object segmentation, the color feature is applied to find out the region of the object. After the region of the object is determined, a fast randomized circle detection method is used by checks if there have enough number radius which are the same in a circle in the region. Because of the double recognition, this system can improve the precision for detecting a colored ball. The proposed method is tested on a home security robot to find a ball. The experimental results illustrate the effectiveness of the proposed method.

[1]  Erkki Oja,et al.  Randomized hough transform (rht) : Basic mech-anisms, algorithms, and computational complexities , 1993 .

[2]  E. R. Davies,et al.  Machine vision - theory, algorithms, practicalities , 2004 .

[3]  Alfredo Petrosino,et al.  Circle detection based on orientation matching , 2001, Proceedings 11th International Conference on Image Analysis and Processing.

[4]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[5]  Rafael C. Gonzales,et al.  Digital Image Processing -3/E. , 2012 .

[6]  Tony Lindeberg,et al.  Edge Detection and Ridge Detection with Automatic Scale Selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Karim Faez,et al.  Fast Circle Detection Using Gradient Pair Vectors , 2003, DICTA.

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  A Macfarlane.  THE PYTHAGOREAN THEOREM. , 1911, Science.

[10]  Ling-Hwei Chen,et al.  A fast ellipse/circle detector using geometric symmetry , 1995, Pattern Recognit..

[11]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[12]  Hong Chen,et al.  An effective non-HT circle detection for centers and radii , 2011, 2011 International Conference on Machine Learning and Cybernetics.

[13]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[14]  Xuelong Li,et al.  Insignificant shadow detection for video segmentation , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[15]  James M. Keller,et al.  Image Processing and Computer Vision , 1999 .

[16]  Christopher M. Brown.  Inherent Bias and Noise in the Hough Transform , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Erkki Oja,et al.  A new curve detection method: Randomized Hough transform (RHT) , 1990, Pattern Recognit. Lett..

[18]  Chung-Cheng Chiu,et al.  A Robust Object Segmentation System Using a Probability-Based Background Extraction Algorithm , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[19]  Kuo-Liang Chung,et al.  An Efficient Randomized Algorithm for Detecting Circles , 2001, Comput. Vis. Image Underst..

[20]  Cataldo Guaragnella,et al.  A new algorithm for ball recognition using circle Hough transform and neural classifier , 2004, Pattern Recognit..