Title :
Three-dimensional object recognition using cross-sections
Author_Institution :
Dept. of Electr. & Comput. Eng., Ohio Univ., Athens, OH, USA
Abstract :
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
Keywords :
image matching; object recognition; 3D object recognition; computer-generated surfaces; cross-section boundary gradient; cross-sectional binary images; minimum average cross-sectional difference; region alignment; regions of interest; serial cross-sections; successive slices; Computational modeling; Computer simulation; Image reconstruction; Interpolation; Layout; Mathematical model; Object recognition; Shape measurement; Surface reconstruction; Testing;
Conference_Titel :
System Theory, 1995., Proceedings of the Twenty-Seventh Southeastern Symposium on
Conference_Location :
Starkville, MS
Print_ISBN :
0-8186-6985-3
DOI :
10.1109/SSST.1995.390611
