Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
