Integrating Image Computation in Undergraduate Level Data-Structure Education
Document Type
Article
Publication Date
1998
Keywords
Data structures, computer vision, image processing, linked lists, trees, graphs, hash tables, undergraduate education
Digital Object Identifier (DOI)
https://doi.org/10.1142/S0218001498000609
Abstract
There is a growing need for expertise both in image analysis and in software engineering. To date, these two areas have been taught separately in an undergraduate computer and information science curriculum. However, we have found that introduction to image analysis can be easily integrated in data-structure courses without detracting from the original goal of teaching data structures. Some of the image processing tasks offer a natural way to introduce basic data structures such as arrays, queues, stacks, trees and hash tables. Not only does this integrated strategy expose the students to image related manipulations at an early stage of the curriculum but it also imparts cohesiveness to the data-structure assignments and brings them closer to real life. In this paper we present a set of programming assignments that integrates undergraduate data-structure education with image processing tasks. These assignments can be incorporated in existing data-structure courses with low time and software overheads. We have used these assignment sets thrice: once in a 10-week duration data-structure course at the University of California, Santa Barbara and the other two times in 15-week duration courses at the University of South Florida, Tampa.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
International Journal of Pattern Recognition and Artificial Intelligence, v. 12, issue 8, p. 1071-1080
Scholar Commons Citation
Sarkar, Sudeep and Goldgof, Dmitry, "Integrating Image Computation in Undergraduate Level Data-Structure Education" (1998). Computer Science and Engineering Faculty Publications. 143.
https://digitalcommons.usf.edu/esb_facpub/143
