Adapting Laplacian based filtering in digital image processing to a retina-inspired analog image processing circuit

In this paper, a unique biologically inspired retina circuit architecture providing Laplacian filter based analog image processing has been suggested. A digital image filtering method is utilized for this aim. Convolution theory and masking technique have an important place among digital image processing methods. These two mathematical operations can be easily done with basic electronic circuit structures. We use current mirrors and current subtractor circuit for the purpose of performing convolution by the use of masking technique on any image. The concept of human retina is able to be mimicked by the help of using silicon circuits. A retina construction can be thought as a group of pixel structures. Because of this reason, we first design a novel pixel circuit as a subcircuit for the retina structure. Our new retina-inspired neuromorphic pixel consists of only 8 MOS transistors. Then, 10 k identical pixel circuits are united together with the help of proper subcircuit connections to achieve a retina structure of size 100 x 100 pixels which enables edge detection feature on images thanks to Laplacian filtering. We compare the analysis results of our grid retina circuit with the theoretical Laplacian filter method used in digital image processing. We obtain analysis results of four different grayscale images that agree well with the expected theoretical results for Laplacian filtering.