Izvorni znanstveni članak
https://doi.org/10.7305/automatika.2014.01.317
CPU, GPU and FPGA Implementations of MALD: Ceramic Tile Surface Defects Detection Algorithm
Tomislav Matić
; Computer and Software Engineering Department, Faculty of Electrical Engineering, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2B, 31000 Osijek, Croatia
Ivan Aleksi
orcid.org/0000-0002-6027-7736
; Computer and Software Engineering Department, Faculty of Electrical Engineering, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2B, 31000 Osijek, Croatia
Željko Hocenski
; Computer and Software Engineering Department, Faculty of Electrical Engineering, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2B, 31000 Osijek, Croatia
Sažetak
This paper addresses adjustments, implementation and performance comparison of the Moving Average with Local Difference (MALD) method for ceramic tile surface defects detection. Ceramic tile production process is completely autonomous, except the final stage where human eye is required for defects detection. Recent computational platform development and advances in machine vision provides us with several options for MALD algorithm implementation. In order to exploit the shortest execution time for ceramic tile production process, the MALD method is implemented on three different platforms: CPU, GPU and FPGA, and it is implemented on each platform in at least two ways. Implementations are done in MATLAB’s MEX/C++, C++, CUDA/C++, VHDL and Assembly programming languages. Execution times are measured and compared for different algorithms and their implementations on different computational platforms.
Ključne riječi
CUDA; FPGA; GPU; Integral Image; MALD; Ceramic Tile
Hrčak ID:
118927
URI
Datum izdavanja:
27.2.2014.
Posjeta: 2.654 *