Abstract
Digital Image processing has been a research area of interest in the last decades, standing out for its applications in the analysis of diagnostic images and astronomical images. In this paper, we perform an overview of edge detection methods through finite-difference to present edge detection as a problem-based learning strategy for numerical differentiation, in order to improve the students’ skills in modeling and algorithmic thinking in numerical analysis courses. In addition, we present image restoration through finite-difference as a problem involving partial differential equations and software tools.
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