In recent years, we have experienced an explosion of image gathering modalities along with a resultant increase in the demand for expertise in image related computation. Considerable progress has also been made in fields such as image processing, image analysis, and computer vision. It is no longer sufficient to address this need for image expertise through one or two upper level elective courses in computer vision or image processing. We need to incorporate image related knowledge units in core undergraduate courses such as data structures, introductory programming courses, automata theory, computer ethics, databases, networks, coding theory, and computer algorithms, preferably without major change in the content of these courses. The materials for these knowledge units should be developed so that instructors who are not necessarily computer vision specialists can use them. An added advantage of using image related knowledge units in various courses is that because of their inherent visual nature and large sizes, images offer an excellent medium for the better understanding of underlying core computer science concepts.
Over the past years, we have developed image-related knowledge units, assignments, and software that can be used for introducing image related tasks in undergraduate data structure and algorithms. We make these available for use through this web page. We would appreciate if you would send an email to firstname.lastname@example.org if you use these materials. Proper referencing in published papers etc. is also requested. These materials are available for use for educational or research purposes and are not to be used for commercial purposes.
This work was supported by the National Science Foundation grants IRI-9501932 and DUE-9980832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or the University of South Florida.