Cross-correlation is an important image processing algorithm for template matching widely used on computer vision based systems. This work follows a profile-based hardware/software co-design method to develop an architecture for normalized cross-correlation coefficient calculus using Nios II soft-processor. Results present comparisons between general purpose processor implementation and different customized softprocessor implementation considering execution time and the influence of image and sub-image size. Nios II soft-processors configured with floating-point hardware acceleration achieved a 8.31 speedup. © Springer-Verlag Berlin Heidelberg 2011.
CITATION STYLE
Dias, M. A., & Osorio, F. S. (2011). Hardware/software co-design for image cross-correlation. In Communications in Computer and Information Science (Vol. 165, pp. 161–175). https://doi.org/10.1007/978-3-642-22247-4_14
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