Fast and inexpensive color image segmentation for interactive robots

J. Bruce, Tucker Balch, and Manuela Veloso
Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '00), October, 2000, pp. 2061 - 2066.


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Abstract
Vision systems employing region segmentation by color are crucial in real-time mobile robot applications. With careful attention to algorithm efficiency, fast color image segmentation can be accomplished using commodity image capture and CPU hardware. This paper describes a system capable of tracking several hundred regions of up to 32 colors at 30 Hz on general purpose commodity hardware. The software system consists of: a novel implementation of a threshold classifier, a merging system to form regions through connected components, a separation and sorting system that gathers various region features, and a top down merging heuristic to approximate perceptual grouping. A key to the efficiency of our approach is a new method for accomplishing color space thresholding that enables a pixel to be classified into one or more, up to 32 colors, using only two logical AND operations. The algorithms and representations are described, as well as descriptions of three applications in which it has been used.

Notes
Associated Lab(s) / Group(s): MultiRobot Lab

Text Reference
J. Bruce, Tucker Balch, and Manuela Veloso, "Fast and inexpensive color image segmentation for interactive robots," Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '00), October, 2000, pp. 2061 - 2066.

BibTeX Reference
@inproceedings{Balch_2000_3584,
   author = "J. Bruce and Tucker Balch and Manuela Veloso",
   title = "Fast and inexpensive color image segmentation for interactive robots",
   booktitle = "Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '00)",
   pages = "2061 - 2066",
   month = "October",
   year = "2000",
   volume = "3",
}