A Practical Digital Image Processing Course with morph.py

• Francisco de Assis Zampirolli Universidade Federal do ABC https://orcid.org/0000-0002-7707-1793
• João Marcelo Borovina Josko Universidade Federal do ABC https://orcid.org/0000-0002-8654-5866
• Fernando Teubl Universidade Federal do ABC
• Celso Setsuo Kurashima Universidade Federal do ABC https://orcid.org/0000-0002-3858-2814

DOI: https://doi.org/10.5753/educomp.2024.237274

Resumo

Teaching Digital Imaging Processing (DIP) is challenging, primarily because of its mathematical and algorithms complexities. Despite the recent growth in the field, comprehensive resources are lacking to support DIP education. To address this gap, this paper introduces a practical course utilizing a Python library named morph.py designed for beginners and accessible on Google Colab. This interactive course employs illustrative examples and hands-on exercises to facilitate the learning of fundamental DIP concepts and operators. It begins with basic concepts (e.g., image representation) and progresses to more advanced topics, including image transformations and feature extraction. We conducted an exploratory case study in one group (N=15) and gathered their perception through a voluntary survey. Our quantitative analysis strongly supports our teaching method's effectiveness based on the morph.py library, which addresses the difficulties of teaching DIP to beginners.

Palavras-chave: Computing Education, Digital Image Processing, Colab

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