Contour Object Generation in Object Recognition Manufacturing Tasks

摘要

The article presents a method for obtaining the contour of an object in real time from not binarized images and for objects that can be assembled on line in automated manufacturing processes. The contour information is integrated into a descriptive vector called [BOFnew], which is used by a neural network model of the type FuzzyARTMAP to test the feasibility of the method using the generated contour to learn of the object and then recognize it later To this end, it requires a fast and robust method to acquire process and communicate to a robot the information about positioning and orientation of an object for assembly purposes. The used algorithm and its simulation was developed in MatLab 7.0. Having this method for object recognition manufacturing tasks improves this methodology and allows the implementation of these algorithms in FPGA 's, which gives in manufacturing cell a real possibility performance demanded by industrial environments.