An all-digital ring-wedge detector system is presented that simulates the analog multielement array commonly used in coherent optoelectronic processors. The system is applicable with either hard-copy or digital imagery. Using neural-network software, we demonstrate high accuracy for the recognition of fingerprints, including both orientation and wide-scale size-independent sortings by using ring-only and wedge-only input neurons, respectively. Also, the system is applied on windowed subregions of fingerprint imagery, providing a feature set that summarizes localized information about spatial-frequency content and edge-angle correlations. Examples are presented in which this localized spatial-frequency information is used to produce local ridge-orientation maps and to detect regions of poor print quality. In summary, both direct-image data and spatial-transform data are found to be important.
© 1999 Optical Society of America
(100.2000) Image processing : Digital image processing
(100.5010) Image processing : Pattern recognition
(100.5760) Image processing : Rotation-invariant pattern recognition
(200.4260) Optics in computing : Neural networks
(350.6980) Other areas of optics : Transforms
David M. Berfanger and Nicholas George, "All-Digital Ring-Wedge Detector Applied to Fingerprint Recognition," Appl. Opt. 38, 357-369 (1999)