This paper describes a vision-based system that is able to automatically recognize deformable objects, to estimate their pose, and to select suitable picking points. A hierarchical self-organized neural network is used to segment color images based on texture information. A morphological analysis allows the recognition of the objects and the picking points extraction. The proposed approach is useful in all of the situations where texture properties are significant for detecting regions of interest on deformable objects. Several tests on a large number of images, acquired in real operative working conditions, demonstrate the effectiveness of the system.
Automatic Visual Recognition of Deformable Objects for Grasping and Manipulatio
FORESTI, Gian Luca;
2004-01-01
Abstract
This paper describes a vision-based system that is able to automatically recognize deformable objects, to estimate their pose, and to select suitable picking points. A hierarchical self-organized neural network is used to segment color images based on texture information. A morphological analysis allows the recognition of the objects and the picking points extraction. The proposed approach is useful in all of the situations where texture properties are significant for detecting regions of interest on deformable objects. Several tests on a large number of images, acquired in real operative working conditions, demonstrate the effectiveness of the system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
