You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
Chapter 4: Visual Metrics: Discriminative Power through Flexibility
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print format on
SPIE.org.
Abstract
An important stage in visual processing is the quantification of optical attributes of the outside world. We argue that the metrics used for this quantification are flexible, and that this flexibility is exploited to optimize the discriminative power of the metrics. We derive mathematical expressions for such optimal metrics and show that they exhibit properties resembling well-known visual phenomena. To conclude, we discuss some of the implications of flexible metrics for visual identification.
Online access to SPIE eBooks is limited to subscribing institutions.