Title :
A vision system to identify occluded industrial parts
Author :
Koch, Mark W. ; Kashyap, R.L.
Author_Institution :
Purdue University, West Lafayette, IN.
Abstract :
A vision system is presented that recognizes occluded industrial parts. The unknown image may contain multiple objects that may touch or overlap giving rise to partial occlusion. The vision system uses stored models to locate and identify the objects in the scene. The models are based on the boundary of the object, since we assume that the objects are rigid and planar. From the polygon approximation of the boundary, vertices of high curvature are identified as "corners." These corners are used as features in detecting the model in the image. A globally consistent coordinate transform that takes the model into the image is found by using a Hough like transform and the corner features.
Keywords :
Assembly; Computer vision; Degradation; Feeds; Image recognition; Layout; Machine vision; Marine vehicles; Needles; Object recognition;
Conference_Titel :
Robotics and Automation. Proceedings. 1985 IEEE International Conference on
DOI :
10.1109/ROBOT.1985.1087319