The processing of images is currently moving from desktop implementation to mobile or embedded ones. In the case of automotive image processing, limited resources in memory or CPU frequency reduce the applicability of nowadays algorithms and possibility of real time processing. In this respect, we have proposed two methods for fast computation of edge detection. The accuracy and speedup were compared with some of basic methods as Canny and Sobel detectors. Also for a solid reference, the Berkeley Computer Vision Group datasets were employed as benchmarks. Good results were obtained over one hundred images from the set. In view of an embedded implementation, two platforms were used for the evaluation of the proposed methods and the references. Performing two times faster and with similar accuracy, our algorithms could have evident implementations in the growing field of embedded devices.
edge detection; algorithm complexity; real time computation; embedded systems
Syed Usama KHALID BUKHARI, Remus BRAD, Constantin BĂLĂ - ZAMFIRESCU, "Fast Edge Detection Algorithm for Embedded Systems", Studies in Informatics and Control, ISSN 1220-1766, vol. 23(2), pp. 163-169, 2014. https://doi.org/10.24846/v23i2y201404
All articles published by Studies in Informatics and Control (SIC) are published in accordance with the terms and conditions of the Creative Commons Attribution License (CC BY-NC-SA 4.0).