Abstract:
Efficient and robust information retrieval from large image
databases is an essential functionality for the reuse,
manipulation, and editing of multimedia documents.
Structural feature indexing is a potential approach to
efficient shape retrieval from large databases, but it is
sensitive to noise, scales of observation, and local shape
deformations. To improve the robustness, shape feature
generation techniques are incorporated into structural
feature indexing. The feature transformation rules
obtained by an analysis of some particular types of shape
deformations are exploited to generate features that can be
extracted from deformed patterns. Experimental trials with
large image databases of boundary contours show that the
feature generation significantly improves robustness and
efficiency of shape retrieval.