Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1408-187
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 and 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.
Keywords
Average magnitude difference function, field programmable gate arrays, histogram of oriented gradients, image processing
First Page
4368
Last Page
4382
Recommended Citation
PEKER, MURAT; ALTUN, HALİS; and KARAKAYA, FUAT
(2016)
"Hardware implementation of a scale and rotation invariant object detection algorithm on FPGA for real-time applications,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 24:
No.
5, Article 77.
https://doi.org/10.3906/elk-1408-187
Available at:
https://journals.tubitak.gov.tr/elektrik/vol24/iss5/77
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons
