Separable convolution gaussian smoothing filters on a xilinx FPGA platform

Convolution Gaussian filtering is a technique that can be used for a wide array of image processing tasks, some of which may include smoothing, edge detection, line parameter estimation and texture analysis. The greatest advantage of the Gaussian filters is that they are separable. Our main goal in this paper is to develop an efficient architecture for Separable Gaussian smoothing filters using intermediate controller based on Finite State Machine simulated in VHDL and prototyped on device technology of XILINX VirtexV FPGA platform. The proposed separable filtering approach is significantly faster and occupied few resources in terms of number of clock cycles and number of multipliers compared to the general two-dimensional convolution implementation. This difference is very important for larger mask sizes because hardware complexity is widely reduced.