Reduced Image Noise on Shape Recognition Using Singular Value Decomposition forPick and Place Robotic Systems

This paper presents reduced image noise on shape recognition by incorporating singular value decomposition. The singular value decomposition is used for image noise reduction for pick and place robotic system. It is possible to find the best approximation of the original data points using fewer dimensions; hereby, processing the edges of the image by smoothening. Experimental studies have been carried out to verify the effectiveness of the proposed scheme. The graphical user interface (GUI) uses the image acquisition toolbox of Matlab and it is used to capture the image. The object borders are decomposed into the vector points in the form of matrix. Results have shown that the proposed method is effective and the robotic arm then enables to determine the object through various tests of the different shapes. By using the proposed scheme, additional functions can be added such as monitoring, roaming, etc. leading to a smart pick and place robotic system.