Performance Analysis of Neural Network Model for Automated Visual Inspection with Robotic Arm Controller System

Abstract

The concept of Automated Visual Inspection (AVI) have emerged as a powerful platform for industrial machine vision where it used to inspect a large number of products rapidly. However, a major problem with this kind of application is the quality produced by the recognition process. In this paper, a system with the capability of identifying and categorizing a product based on image processing has been implemented. The image was processed by using Radial Basis Function (RBF) based on output center and spread values optimization. Robotic arm controller developed for pick and place the product based on their categories. Two performance measures are used to validate the model classification range and the spread values. The results of this project indicate that the model used able to identify the product and classify it according to their shape.