Recognition of Cylindrical Objects Using Occluding Boundaries Obtained from Colour Based Segmentation | Zendy

Dekun Yang | Zendy; Josef Kittler | Zendy; George Matas | Zendy

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Recognition of Cylindrical Objects Using Occluding Boundaries Obtained from Colour Based Segmentation

Author(s) -

Dekun Yang,

Josef Kittler,

George Matas

Publication year - 1994

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.8.43

Subject(s) - artificial intelligence , computer vision , segmentation , boundary (topology) , image segmentation , computer science , object (grammar) , constraint (computer aided design) , cognitive neuroscience of visual object recognition , enhanced data rates for gsm evolution , edge detection , pattern recognition (psychology) , plane (geometry) , object detection , ground plane , scale space segmentation , image (mathematics) , image processing , mathematics , geometry , mathematical analysis , telecommunications , antenna (radio)

This paper describes a method for model-based recognition of cylindrical objects from occluding boundaries obtained by computationally efficient colour segmentation of a 2D image. The models are invoked by combining geometric and colour features. Occluding boundaries of hypothesized objects are generated using colour segmentation and ground plane constraint. Hypothesis verification is achieved by evaluating the fit between occluding boundary generated by the hypothesised object and the edge data. This method differs from existing methods in that it integrates multiple measurements and prior knowledge to achieve robust object recognition. Experiments with real images have been carried out and the results are promising.

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