Title :
A Model-Based Vision System for Industrial Parts
Author_Institution :
Department of Computer Science, Research Laboratories, General Motors Corporation
Abstract :
A vision system has been developed which can determine the position and orientation of complex curved objects in gray-level noisy scenes. The system organizes and reduces the image data from a digitized picture to a compact representation having the appearance of a line drawing. This compact image representation can be used for forming a model under favorable viewing conditions or for locating a part under poor viewing conditions by a matching process that uses a previously formed model. Thus, models are formed automatically by having the program view the part under favorable lighting and background conditions. The compact image representation describes the boundaries of the part.
Keywords :
Computer vision; image analysis; learning system; model-based vision; pattern recognition; scene analysis; vision for industrial parts; Computer vision; Image analysis; Image representation; Image texture analysis; Layout; Learning systems; Machine vision; Pattern analysis; Pattern recognition; TV; Computer vision; image analysis; learning system; model-based vision; pattern recognition; scene analysis; vision for industrial parts;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/TC.1978.1675046
