Hardware emulation of HOG and AMDF based scale and rotation invariant robust shape detection

Abstract

In this study, a hardware emulation of HOG and AMDF based scale and rotation invariant robust shape detection for Field Programmable Gate Arrays (FPGA) is described. For this purpose, a robust algorithm with light-computational load has been developed based on features extracted from histogram of oriented gradients (HOG). A normalization scheme is proposed to obtain scale-invariant robust features using HOG algorithm. Also a novel method for shape detection is proposed using Average Magnitude Difference Function (AMDF) which leads to a rotation-invariant and computationally light shape detection method. It is shown that the proposed method is robust against noise as well. Also it is indicated that the performance of the method is highly satisfactory for implementation on real-life industrial problems.