We propose a class of generalized moment functions (GMFs) that can be used to determine a set of geometric points, namely, generalized centroids (G centroids), within an object. Based on a linear GMF, a mass centroid and its subcentroids can be defined and extracted, which provide information on the location and orientation of an object. Similar to traditional moment functions, GMFs can also be used to describe the global shape of an object, including symmetry and fullness. However, GMFs, along with G centroids and subcentroids, can further serve to construct a feature vector of an object, which is critical for image registration and invariant pattern recognition. One can extract more distinguishing features from the same object by changing the combination of GMFs. We present results that show simulations of pattern recognition from uniform backgrounds.

© 2005 Optical Society of America

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
Log in to access OSA Member Subscription

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
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Article level metrics 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
Log in to access OSA Member Subscription

Related Journal Articles

• All-Digital Ring-Wedge Detector Applied to Fingerprint Recognition (AO)
• Invariant Pattern Recognition Based on Centroids (AO)
• Generalized circular autoregressive models for isotropic and anisotropic Gaussian textures (JOSAA)
• Nonlinear Correlation for Estimating the Motion of Multiple Objects in Image Sequences (AO)
• Phase unwrapping using an extrapolation-projection algorithm (JOSAA)

Related Conference Papers

• Integrated System Design for Application-Specific Imaging
• Automatic classification of biological specimens: Diatoms
• Joint Spectral-Spatial Pattern Recognition and Target Segregation
• Joint Spectral-Spatial Pattern Recognition and Target Segregation
• Joint Spectral-Spatial Pattern Recognition and Target Segregation