Artikel,
Computational strategies for object recognition
ACM Comput. Surv., 24 (1): 5--62 (1992)
DOI: http://proxy.bib.uottawa.ca:3207/10.1145/128762.128763
Zusammenfassung
This article reviews the available methods for automated identification
of objects in digital images. The techniques are classified into
groups according to the nature of the computational strategy used.
Four classes are proposed: (1) the simplest strategies, which work
on data appropriate for feature vector classification, (2) methods
that match models to symbolic data structures for situations involving
reliable data and complex models, (3) approaches that fit models
to the photometry and are appropriate for noisy data and simple models,
and (4) combinations of these strategies, which must be adopted in
complex situations. Representative examples of various methods are
summarized, and the classes of strategies with respect to their appropriateness
for particular applications.
