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Proceedings Paper

Formal system specification and testing of image processing/computer vision algorithms
Author(s): Andrew C. Segal; John Quintas; Robert Kero; Richard Greene; Greg Chisholm
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Paper Abstract

An important issue in the advancement of Image Processing and Computer Vision (IP/CV) algorithm development is the ability to test, verify and compare the newly developed algorithm performance to other functionally equivalent algorithms and to ground truth in a complete and meaningful way. In this paper, we explore several criteria to estimate the performance of IP/CV algorithms against databases of synthetic and real data and use statistical analysis to determine performance. Formal system analysis along with Monte Carlo testing is used to rigorously compare these algorithms. A case study is performed on the familiar edge detection algorithms to illustrate the techniques and also the vulnerability of these algorithms to good average performance but in certain cases to very poor performance.

Paper Details

Date Published: 4 August 1993
PDF: 6 pages
Proc. SPIE 1909, Device-Independent Color Imaging and Imaging Systems Integration, (4 August 1993); doi: 10.1117/12.149064
Show Author Affiliations
Andrew C. Segal, Univ. of Illinois/Chicago (United States)
John Quintas, Univ. of Illinois/Chicago (United States)
Robert Kero, Argonne National Labs. (United States)
Richard Greene, Argonne National Labs. (United States)
Greg Chisholm, Argonne National Labs. (United States)

Published in SPIE Proceedings Vol. 1909:
Device-Independent Color Imaging and Imaging Systems Integration
Ricardo J. Motta; Hapet A. Berberian, Editor(s)

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