Affine-invariant feature vector (Ip and Shen Image Vision Comput. 16 (2) (1
998) 135-146). that captures both local and semi-local geometric features a
round each point of the object boundary is applied here for the detection o
f skewed symmetries. Based on the affine-invariant shape representation, th
e problem of detecting symmetry axes has been formulated as a problem of de
tecting lines, with known orientations, in a local similarity matrix of an
object. Since the feature vector extracts sufficient local and semi-local s
hape information For every point along the object boundary, the process of
checking symmetric point pairs is thus robust against both noises and defor
mations. Moreover, our technique is able to detect all the local reflection
al symmetries contained in the object. Various experimental results have sh
own the robustness and effectiveness of our method in detecting skewed symm
etries from both self-symmetric objects and generalized objects. (C) 2001 P
attern Recognition Society, Published by Elsevier Science Ltd. All rights r
eserved.