Hardware implementation of a scale and rotation invariant object detection algorithm on FPGA for real-time applications
Peker, Murat and Altun, Halis and Karakaya, Fuat
Loading
Abstract
A hardware implementation of a computationally light, scale, and
rotation invariant method for shape detection on FPGA is devised. The
method is based on histogram of oriented gradients (HOG) and average
magnitude difference function (AMDF). AMDF is used as a decision module
that measures the similarity/dissimilarity between HOG vectors of an
image in order to classify the object. In addition, a simulation
environment implemented on MATLAB is developed in order to overcome the
time-consuming andd tedious process of hardware verification on the FPGA
platform. The simulation environment provides specific tools to quickly
implement the proposed methods. It is shown that the simulator is able
to produce exactly the same results as those obtained from FPGA
implementation. The results indicate that the proposed approach leads to
a shape detection method that is computationally light, scale, and
rotation invariant, and, therefore, suitable for real-time industrial
and robotic vision applications.... Show more Show less