Three-dimensional object recognition using cross-sections
Mehmet Çelenk · 2002
Describes a method for recognizing 3D objects from their serial cross-sections. Object regions of interest in cross-sectional binary images of successive slices are aligned with those of the models. Cross-sectional differences between the object and the models are measured in the direction of the gradient of the cross-section boundary. This is repeated in all the cross-sectional images. The model with minimum average cross-sectional difference is selected as the best match to the given object. The method is tested using computer-generated surfaces, and results are presented.>