Robotic machine vision system for defective screw Identification using Fisher’s LDA Techniques

The research work dedicated for the object identification difficulty resolved by the techniques of principal component analysis (PCA) and linear discriminant analysis (LDA) along with robotic machine vision system. The effectiveness of the proposed model is carefully considered for a case when the pictures of an object like Screw have not initially processed but managed them into a standard form in terms of back-ground, scaling, positioning and adjustment of intensity or brightness. Similarly, when processed a huge amount of image data sets it is necessary to use PCA and LDA for optimizing the computational difficulty. Here using the LDA and PCI the effectiveness of the model is analyzed. By an introducing the robotic machine vision system the identification accuracy can be enhanced to a greater label.