Abstract

Conventional Gabor representation and its extracted features often yield a fairly poor performance in extracting the invariance features of objects. To address this issue, a global Gabor representation method for raised characters pressed on label is proposed in this paper, where the representation only requires few summations on the conventional Gabor filter responses. Features are then extracted from these new representations to construct the invariant features. Experimental results clearly show that the obtained global Gabor features provide good performance in rotation, translation, and scale invariance. Also, they are insensitive to illumination conditions and noise changes. It is proved that Gabor filters can be reliably used in low-level feature extraction in image processing and the global Gabor features can be used to construct robust invariant recognition system.

© 2008 Chinese Optics Letters

PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription