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Description:
In this thesis various approaches to object recognition are investigated, mainly recorded by multiocular imaging systems. The strengths and weaknesses of the approaches are analysed. Several different methods - Template Matching, Feature Pose Maps, Contracting Curve Density, Active Contours - are implemented, thoroughly investigated, and evaluated. These methods make use of images synchronously taken by multiple calibrated cameras in order to improve the location accuracy and to overcome ambiguities. Based on these information a new object recognition and localisation algorithm is designed, implemented, and tested. This algorithm is based on the sign of the gradient of the feature-model distance in the image. Since the model function is reduced to very little information (its sign) at a given feature position, the evaluation is very fast as it can be reduced to a simple table lookup. Thus we named the new method Gradient Sign Tables. In order to conveniently obtain a calibration of an arbitrary number of cameras a new calibration procedure is designed, implemented, and tested that is centred around a reliable, automatic calibration pattern finder. Based on the methods above a three-dimensional object recognition system is designed, implemented, evaluated, and adjusted for selected practical applications. It has the following properties: - The object pose is obtained with application specific degrees of freedom. - The type of an object is automatically determined out of a set of given types with rejection of unknown objects. - Corresponding points between the images and the model of an object are automatically determined. - The implementations of the algorithms fulfil the timing requirements of typical industrial image processing applications. Processing times of at most seconds, but not minutes are achieved. - Moderate requirements are made to the hardware in terms of image resolution and memory consumption. Usually VGA sized camera resolutions are sufficient. - No algorithm or implementation has arbitrary ...